The document discusses using Weka data mining software to analyze economic data from Japan from 1970-2009. It performs three techniques: 1) Decision tree classification using M5P algorithm to predict liquidity based on other economic factors, 2) Linear regression to develop a mathematical model relating variables, 3) Clustering using k-means to group similar data points. The results of each technique are presented and interpreted to understand relationships between economic indicators.
It's not Baymax nor Rosie. Robots are spreading in many sectors, from industry to enterprise and consumer. Presentation given in April 2017 at the Startup Launchpad in Hong Kong.
A robot is an automatically controlled machine that can be programmed to carry out tasks on its own. The field of robotics involves designing, building, and programming robots. Robots are used for tasks that are hazardous, repetitive, or require precision as they can work faster and more accurately than humans. Some key parts of robots include sensors that receive input, effectors and actuators that allow movement, and controllers that direct the robot's behavior. While robots have benefits, they also present issues like potential job losses or use for harmful purposes that need to be addressed.
Peta khg nasional, indikatif fungsi lindung & areal restorasi ekosistem g...Panji Kharisma Jaya
Dokumen tersebut memberikan informasi tentang peta kesatuan hidrologis gambut (KHG) di Indonesia. Dokumen tersebut menjelaskan proses pembuatan peta KHG meliputi interpretasi citra satelit, delineasi batas KHG, verifikasi lapangan, dan penentuan prioritas KHG. Dokumen tersebut juga menyajikan data jumlah dan luas KHG per provinsi di Indonesia.
It's not Baymax nor Rosie. Robots are spreading in many sectors, from industry to enterprise and consumer. Presentation given in April 2017 at the Startup Launchpad in Hong Kong.
A robot is an automatically controlled machine that can be programmed to carry out tasks on its own. The field of robotics involves designing, building, and programming robots. Robots are used for tasks that are hazardous, repetitive, or require precision as they can work faster and more accurately than humans. Some key parts of robots include sensors that receive input, effectors and actuators that allow movement, and controllers that direct the robot's behavior. While robots have benefits, they also present issues like potential job losses or use for harmful purposes that need to be addressed.
Peta khg nasional, indikatif fungsi lindung & areal restorasi ekosistem g...Panji Kharisma Jaya
Dokumen tersebut memberikan informasi tentang peta kesatuan hidrologis gambut (KHG) di Indonesia. Dokumen tersebut menjelaskan proses pembuatan peta KHG meliputi interpretasi citra satelit, delineasi batas KHG, verifikasi lapangan, dan penentuan prioritas KHG. Dokumen tersebut juga menyajikan data jumlah dan luas KHG per provinsi di Indonesia.
Linear regression an 80 year study of the dow jones industrial averageTehyaSingleton
Linear regression was used to model the relationship between the Dow Jones Industrial Average (DJIA) price and years since 1930 over an 80 year period. The results showed a strong positive linear relationship where DJIA price increases by about 125 points for each additional year. The slope of the linear model indicates that DJIA price rises as years since 1930 increases. The y-intercept of the model, which is the hypothetical DJIA price at year 0 (1930), provides meaningful context about the starting price over the 80 years analyzed.
Linear regression an 80 year study of the dow jones industrial averageTehyaSingleton
Linear regression was used to model the relationship between the Dow Jones Industrial Average (DJIA) price and years since 1930 over an 80 year period. The results showed a strong positive linear relationship where DJIA price increases by about 125 points for each additional year. The regression equation determined that DJIA price equals 125.3 times the number of years since 1930 minus 2.4425. While DJIA price has generally increased over the eight decades, the model suggests it would have been negative in 1930 based on the y-intercept value.
This Slideshare presentation is a partial preview of the full business document. To view and download the full document, please go here:
http://flevy.com/browse/business-document/Excel-Model-for-Banking--119
This is a valuation model of Axis bank. This model covers the different valuation types to arrive at the fair value of a stock.
This document provides specifications for Moyno G2 and G3 series pumps including dimensions and weights. It lists various pump frame sizes from 1E008G2 to 6K175G2 with corresponding measurements and discharge weights at different pipe lengths. Key dimensions included are flange size, length and diameter of pump components. The page notes that dimensions are in inches and provides contact information for Moyno pumps.
The document analyzes international trade and finance data for the Philippines from 1983 to 2006. It provides tables showing trade balances, exports and imports by commodity and section over this period. Exports grew substantially from $556 million in 1983 to over $2.4 billion in 2006, while imports increased from $886 million to over $2.7 billion for the same period. The trade balance fluctuated from a surplus of $330 million in 1983 to a deficit of $345 million in 2006. Top exports included electronic products, garments, coconut oil and copper concentrates.
The document contains survey data from a road construction project including coordinates, elevations, cut depths, embankment heights, and volumes of material removed and placed at regular intervals along the road. The data is presented in a table with distance along the road in the first column and corresponding coordinate, elevation, cut, embankment and volume metrics in subsequent columns.
This document provides performance objectives and nutritional recommendations for Cobb500 broilers. It includes target weights, daily gains, feed conversions, and daily feed intake for male and female broilers from hatch to 56 days. Recommended nutrient levels for medium/large and small broilers are also presented. The goals are to help farmers efficiently raise broilers with good livability, welfare, and yield performance through genetic improvements and optimized nutrition programs.
Fundamental Equity Analysis - QMS Advisors HDAX FlexIndex 110BCV
This document provides an overview of analyst recommendations and fundamental analysis for various companies and market indices. It includes metrics such as market capitalization, revenue, earnings per share, price-to-earnings ratios, credit ratings, and revenue/earnings growth estimates for the past year and next few years. The metrics are presented in table format with estimates from analysts to aid in evaluating investment opportunities.
This document summarizes dairy product import data to Colombia from 1991-2011, including the kilograms and US dollar cost of imports for milk powders, evaporated milk, condensed milk, liquid milk, butter, cheeses, whey, and totals. It shows that import quantities and costs generally increased over time, with the largest imports being milk powders, liquid milk, and cheeses.
This document contains algorithms for numerical recipes and statistical equations. It includes algorithms for generating the gamma function, solving ordinary differential equations using Runge-Kutta methods, and generating probability distributions and expected values. The document also contains a table with values of the ratio r/θ for different values of r and θ.
This document provides specifications for various standard H-beam, wide flange, lip channel, and equal angle steel sections. It includes dimensions such as height, width, thickness, area, weight, moments of inertia, radii of gyration, and other geometric properties. Sections range in size from 100x100 mm to 588x300 mm for H-beams, 148x100 mm to 500x200 mm for wide flanges, 100x50x20 mm to 200x75x20 mm for lip channels, and 40x40 mm to 120x120 mm for equal angles. Properties are specified in metric units.
The document contains two tables providing future value interest factors for one dollar and one dollar annuities compounded at various interest rates over different periods of time. Table A-1 shows the future value of $1 invested at rates from 1% to 30% over periods from 1 to 30 years. Table A-2 shows the future value of a $1 annuity invested at the same rates and periods. The tables allow users to determine the future values of single investments and annuities based on the interest rate and time period.
The document contains two tables providing future value interest factors for present values compounded over time at given interest rates. Table A-1 gives the future value of $1 invested for a given number of periods at rates from 1% to 30%. Table A-2 gives the future value of a $1 annuity invested over the same periods and rates. Both tables allow users to determine the future value of investments based on the interest rate and length of time compounded.
The document contains two tables providing future value interest factors for one dollar and one dollar annuities compounded at various interest rates over different periods of time. Table A-1 shows the future value of $1 invested at rates from 1% to 30% over periods from 1 to 30 years. Table A-2 shows the future value of a $1 annuity invested at the same rates and periods. The tables allow users to determine the future values of single investments and annuities based on the interest rate and time horizon.
The document contains two tables providing future value interest factors for present values compounded over time at given interest rates. Table A-1 gives the future value of $1 invested for a given number of periods at rates from 1% to 30%. Table A-2 gives the future value of a $1 annuity invested over the same periods and rates. The tables allow users to calculate future or present values of investments compounded at different rates over different lengths of time.
The document outlines revenue and expenses by line of business for a company in January 2004, showing a total revenue of $259.42 million and total operating expenses of $43.22 million, resulting in operating income of $31.90 million. Cellular commission revenue was the largest source of revenue at $244.27 million while kiosk salary costs were the biggest expense at $58.95 million. The distribution business generated the highest operating income of $24.59 million with an operating margin of 6.5%.
Hyundai hdf15 3 forklift truck service repair manualfjjskekmdmme
This document appears to be a service manual containing sections on general information, removal and installation procedures, various mechanical systems including power train, brake, steering, hydraulic, electrical, and mast systems. Each section contains groups relating to structure, operation, troubleshooting, testing, and disassembly/assembly of components. Specification tables are also included for unit conversions.
Hyundai hdf15 3 forklift truck service repair manualfjjsekmmm
This document outlines the contents and structure of a service manual for a machine. It includes 8 sections that cover general information, removal and installation of components, power train, brake, steering, hydraulic, electrical, and mast systems. Each section contains groups that provide details on the structure, operation, troubleshooting, testing, and disassembly/assembly of the various systems. Specifications, conversions charts for measurements, and a temperature conversion table are also included at the beginning.
Hyundai hdf18 3 forklift truck service repair manualfjjsekmmm
This document outlines the contents and structure of a service manual for a machine. It includes 8 sections that cover general information, removal and installation of components, power train, brake, steering, hydraulic, electrical, and mast systems. Each section contains groups that provide details on the structure, operation, troubleshooting, testing, and disassembly/assembly of the various systems. Specifications, safety hints, and periodic replacement intervals are also addressed.
Hyundai hdf18 3 forklift truck service repair manualfjjskekmdmme
This document appears to be a service manual containing sections on general information, removal and installation procedures, various mechanical systems including power train, brake, steering, hydraulic, electrical, and mast systems. Each section contains groups relating to structure and operation, troubleshooting, tests, adjustments, and disassembly/assembly of components. Specifications and conversion tables for measurements are also provided at the beginning.
Marketing great dakota bank case - Harward Business SchoolShubham Gupta
Our group at Sunstone Business School have come with a short presentation with detailed solution for the Great Dakota Bank case study for Harward case.
Linear regression an 80 year study of the dow jones industrial averageTehyaSingleton
Linear regression was used to model the relationship between the Dow Jones Industrial Average (DJIA) price and years since 1930 over an 80 year period. The results showed a strong positive linear relationship where DJIA price increases by about 125 points for each additional year. The slope of the linear model indicates that DJIA price rises as years since 1930 increases. The y-intercept of the model, which is the hypothetical DJIA price at year 0 (1930), provides meaningful context about the starting price over the 80 years analyzed.
Linear regression an 80 year study of the dow jones industrial averageTehyaSingleton
Linear regression was used to model the relationship between the Dow Jones Industrial Average (DJIA) price and years since 1930 over an 80 year period. The results showed a strong positive linear relationship where DJIA price increases by about 125 points for each additional year. The regression equation determined that DJIA price equals 125.3 times the number of years since 1930 minus 2.4425. While DJIA price has generally increased over the eight decades, the model suggests it would have been negative in 1930 based on the y-intercept value.
This Slideshare presentation is a partial preview of the full business document. To view and download the full document, please go here:
http://flevy.com/browse/business-document/Excel-Model-for-Banking--119
This is a valuation model of Axis bank. This model covers the different valuation types to arrive at the fair value of a stock.
This document provides specifications for Moyno G2 and G3 series pumps including dimensions and weights. It lists various pump frame sizes from 1E008G2 to 6K175G2 with corresponding measurements and discharge weights at different pipe lengths. Key dimensions included are flange size, length and diameter of pump components. The page notes that dimensions are in inches and provides contact information for Moyno pumps.
The document analyzes international trade and finance data for the Philippines from 1983 to 2006. It provides tables showing trade balances, exports and imports by commodity and section over this period. Exports grew substantially from $556 million in 1983 to over $2.4 billion in 2006, while imports increased from $886 million to over $2.7 billion for the same period. The trade balance fluctuated from a surplus of $330 million in 1983 to a deficit of $345 million in 2006. Top exports included electronic products, garments, coconut oil and copper concentrates.
The document contains survey data from a road construction project including coordinates, elevations, cut depths, embankment heights, and volumes of material removed and placed at regular intervals along the road. The data is presented in a table with distance along the road in the first column and corresponding coordinate, elevation, cut, embankment and volume metrics in subsequent columns.
This document provides performance objectives and nutritional recommendations for Cobb500 broilers. It includes target weights, daily gains, feed conversions, and daily feed intake for male and female broilers from hatch to 56 days. Recommended nutrient levels for medium/large and small broilers are also presented. The goals are to help farmers efficiently raise broilers with good livability, welfare, and yield performance through genetic improvements and optimized nutrition programs.
Fundamental Equity Analysis - QMS Advisors HDAX FlexIndex 110BCV
This document provides an overview of analyst recommendations and fundamental analysis for various companies and market indices. It includes metrics such as market capitalization, revenue, earnings per share, price-to-earnings ratios, credit ratings, and revenue/earnings growth estimates for the past year and next few years. The metrics are presented in table format with estimates from analysts to aid in evaluating investment opportunities.
This document summarizes dairy product import data to Colombia from 1991-2011, including the kilograms and US dollar cost of imports for milk powders, evaporated milk, condensed milk, liquid milk, butter, cheeses, whey, and totals. It shows that import quantities and costs generally increased over time, with the largest imports being milk powders, liquid milk, and cheeses.
This document contains algorithms for numerical recipes and statistical equations. It includes algorithms for generating the gamma function, solving ordinary differential equations using Runge-Kutta methods, and generating probability distributions and expected values. The document also contains a table with values of the ratio r/θ for different values of r and θ.
This document provides specifications for various standard H-beam, wide flange, lip channel, and equal angle steel sections. It includes dimensions such as height, width, thickness, area, weight, moments of inertia, radii of gyration, and other geometric properties. Sections range in size from 100x100 mm to 588x300 mm for H-beams, 148x100 mm to 500x200 mm for wide flanges, 100x50x20 mm to 200x75x20 mm for lip channels, and 40x40 mm to 120x120 mm for equal angles. Properties are specified in metric units.
The document contains two tables providing future value interest factors for one dollar and one dollar annuities compounded at various interest rates over different periods of time. Table A-1 shows the future value of $1 invested at rates from 1% to 30% over periods from 1 to 30 years. Table A-2 shows the future value of a $1 annuity invested at the same rates and periods. The tables allow users to determine the future values of single investments and annuities based on the interest rate and time period.
The document contains two tables providing future value interest factors for present values compounded over time at given interest rates. Table A-1 gives the future value of $1 invested for a given number of periods at rates from 1% to 30%. Table A-2 gives the future value of a $1 annuity invested over the same periods and rates. Both tables allow users to determine the future value of investments based on the interest rate and length of time compounded.
The document contains two tables providing future value interest factors for one dollar and one dollar annuities compounded at various interest rates over different periods of time. Table A-1 shows the future value of $1 invested at rates from 1% to 30% over periods from 1 to 30 years. Table A-2 shows the future value of a $1 annuity invested at the same rates and periods. The tables allow users to determine the future values of single investments and annuities based on the interest rate and time horizon.
The document contains two tables providing future value interest factors for present values compounded over time at given interest rates. Table A-1 gives the future value of $1 invested for a given number of periods at rates from 1% to 30%. Table A-2 gives the future value of a $1 annuity invested over the same periods and rates. The tables allow users to calculate future or present values of investments compounded at different rates over different lengths of time.
The document outlines revenue and expenses by line of business for a company in January 2004, showing a total revenue of $259.42 million and total operating expenses of $43.22 million, resulting in operating income of $31.90 million. Cellular commission revenue was the largest source of revenue at $244.27 million while kiosk salary costs were the biggest expense at $58.95 million. The distribution business generated the highest operating income of $24.59 million with an operating margin of 6.5%.
Hyundai hdf15 3 forklift truck service repair manualfjjskekmdmme
This document appears to be a service manual containing sections on general information, removal and installation procedures, various mechanical systems including power train, brake, steering, hydraulic, electrical, and mast systems. Each section contains groups relating to structure, operation, troubleshooting, testing, and disassembly/assembly of components. Specification tables are also included for unit conversions.
Hyundai hdf15 3 forklift truck service repair manualfjjsekmmm
This document outlines the contents and structure of a service manual for a machine. It includes 8 sections that cover general information, removal and installation of components, power train, brake, steering, hydraulic, electrical, and mast systems. Each section contains groups that provide details on the structure, operation, troubleshooting, testing, and disassembly/assembly of the various systems. Specifications, conversions charts for measurements, and a temperature conversion table are also included at the beginning.
Hyundai hdf18 3 forklift truck service repair manualfjjsekmmm
This document outlines the contents and structure of a service manual for a machine. It includes 8 sections that cover general information, removal and installation of components, power train, brake, steering, hydraulic, electrical, and mast systems. Each section contains groups that provide details on the structure, operation, troubleshooting, testing, and disassembly/assembly of the various systems. Specifications, safety hints, and periodic replacement intervals are also addressed.
Hyundai hdf18 3 forklift truck service repair manualfjjskekmdmme
This document appears to be a service manual containing sections on general information, removal and installation procedures, various mechanical systems including power train, brake, steering, hydraulic, electrical, and mast systems. Each section contains groups relating to structure and operation, troubleshooting, tests, adjustments, and disassembly/assembly of components. Specifications and conversion tables for measurements are also provided at the beginning.
Marketing great dakota bank case - Harward Business SchoolShubham Gupta
Our group at Sunstone Business School have come with a short presentation with detailed solution for the Great Dakota Bank case study for Harward case.
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The document discusses segmenting voters for a political campaign. It proposes segmenting the constituency by geographic region, age, past voting habits, and beliefs/values. The key segments identified are: people aged 18-35 living in developed areas with high voter turnout who share the candidate's beliefs; people aged 35-60 in developed high turnout areas; and people aged 60+ in developed high turnout areas. Marketing plans target these groups through social media, TV/newspapers, rallies, and home visits. Groups with different beliefs or low turnout will receive less focus.
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The document discusses Bose Corporation's JIT II program with its suppliers. It recommends that Bose should continue with the JIT II approach rather than become vertically integrated. The JIT II program involves suppliers sending representatives to work as buyers within Bose plants. This provides benefits like reduced costs, improved communication between Bose and suppliers, and faster response to scheduling changes. The program streamlines the procurement process and allows for stronger supplier alliances. Both Bose and its suppliers see continued benefits from the unique JIT II arrangement years after its implementation.
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Explore the details in our newly released product manual, which showcases NEWNTIDE's advanced heat pump technologies. Delve into our energy-efficient and eco-friendly solutions tailored for diverse global markets.
Discover timeless style with the 2022 Vintage Roman Numerals Men's Ring. Crafted from premium stainless steel, this 6mm wide ring embodies elegance and durability. Perfect as a gift, it seamlessly blends classic Roman numeral detailing with modern sophistication, making it an ideal accessory for any occasion.
https://rb.gy/usj1a2
How are Lilac French Bulldogs Beauty Charming the World and Capturing Hearts....Lacey Max
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Dpboss Matka Guessing Satta Matta Matka Kalyan Chart Satta Matka
DATA MINING WITH WEKA
1. Term paper on Data mining
How to use Weka for data analysis
Submitted by: Shubham Gupta (10BM60085)
Vinod Gupta School of Management
2. The first technique that we would do on weka is classification. The data below shows the financial
situation in Japan. The data has been collected from 1970-2009. The columns represent:
1) BROAD: Broad money supplied in the economy
2) DOMC: Domestic consumption
3) PSC: Payment securities
4) CLAIMS: Represents the claims on the government.
5) TOTRES: Total Reserves
6) GDP: Gross domestic product
7) LIQLB: Liquid Liability
We want to get a decision tree that would help us decide what values of independent variable may
result in what final rule or result. For example if we know that for a DOMC> 140 and PSC> 150.3 we
would always get say GDP of greater than 3 trillion yen, then it would help us in making our decisions
better. Hence to get such rules we perform this analysis to generate a decision tree.
YEAR BROAD CLAIMS DOMC PSC TOTRES LIQLB GDP
1970 83.65 61.88 134.25 111.75 4876114550 104.73 205,995,000,000
1971 106.70 21.37 147.59 123.72 15469150615 118.21 232,681,000,000
1972 116.14 23.17 160.29 133.47 18932675966 129.03 308,137,000,000
1973 116.02 19.84 157.87 132.20 13723930639 126.07 418,640,000,000
1974 113.08 13.72 154.00 126.49 16551248298 120.50 464,705,000,000
1975 118.31 13.02 164.40 129.96 14910849997 127.56 505,317,000,000
1976 122.40 12.09 169.96 130.63 18590784646 131.20 567,926,000,000
1977 125.82 8.76 172.45 128.49 25907710023 133.90 698,968,000,000
1978 130.36 8.56 178.29 127.71 37824744320 139.12 982,078,000,000
1979 135.51 8.19 183.05 129.23 31926244737 142.67 1,022,190,000,000
1980 137.95 8.09 188.44 131.29 38918848626 144.30 1,071,000,000,000
1981 142.13 8.04 194.09 134.10 37839039769 150.03 1,183,790,000,000
1982 149.54 7.67 203.99 139.59 34403732201 156.18 1,100,410,000,000
1983 156.55 6.72 213.12 145.03 33844549531 162.92 1,200,190,000,000
1984 159.31 6.69 217.77 147.43 33898638541 165.34 1,275,560,000,000
1985 160.68 7.66 220.09 149.90 34641202378 167.41 1,364,160,000,000
1986 167.30 7.67 230.23 156.30 51727320082 174.65 2,020,890,000,000
1987 175.85 12.27 243.85 173.48 92701641597 183.77 2,448,670,000,000
1988 178.70 10.66 251.68 182.52 1.06668E+11 186.47 2,971,030,000,000
1989 182.62 10.13 258.13 190.28 93672771034 192.14 2,972,670,000,000
1990 184.06 8.46 259.15 194.81 87828362969 190.16 3,058,040,000,000
1991 184.35 5.20 257.54 195.40 80625855126 189.32 3,484,770,000,000
1992 187.89 4.16 265.33 199.63 79696644593 190.93 3,796,110,000,000
1993 193.97 1.33 274.00 202.14 1.07989E+11 198.16 4,350,010,000,000
1994 200.35 1.88 281.02 204.58 1.35146E+11 204.45 4,778,990,000,000
3. 1995 205.79 1.26 287.13 203.90 1.9262E+11 209.90 5,264,380,000,000
1996 209.72 1.81 292.42 205.21 2.25594E+11 213.63 4,642,540,000,000
1997 215.31 6.47 276.47 217.76 2.26679E+11 221.38 4,261,840,000,000
1998 229.64 1.80 298.40 228.01 2.22443E+11 233.17 3,857,030,000,000
1999 239.91 -1.20 309.92 231.08 2.93948E+11 243.22 4,368,730,000,000
2000 242.24 -1.58 308.91 222.28 3.61639E+11 243.84 4,667,450,000,000
2001 225.31 -33.25 299.43 193.01 4.01958E+11 187.41 4,095,480,000,000
2002 207.79 -4.32 299.16 182.40 4.69618E+11 190.79 3,918,340,000,000
2003 209.70 -1.99 307.26 180.71 6.73554E+11 191.84 4,229,100,000,000
2004 207.51 -1.10 303.48 174.12 8.44667E+11 189.79 4,605,920,000,000
2005 207.24 1.79 312.85 182.87 8.46896E+11 189.30 4,552,200,000,000
2006 204.73 -0.14 304.96 179.99 8.95321E+11 186.06 4,362,590,000,000
2007 201.50 0.16 294.31 172.56 9.73297E+11 184.17 4,377,940,000,000
2008 207.14 0.76 295.42 165.48 1.03076E+12 189.52 4,879,860,000,000
2009 223.76 -1.12 320.53 171.00 1.04899E+12 206.13 5,032,980,000,000
Loading data in Weka is quite easy. Just click on the open file option and give the location of the file.
Figure 1 Shows how to load data in Weka
Weka software is used to classify the above data to find out how these economical factors be modified
or fixed so as to get an 11% growth in the previous year’s GDP
4. Figure 2 Diagram shows where you could the used tree technique
The following shows the output by running the above data in Weka. The Classifier used is to create the
required decision tree is M5P. Weka's M5P algorithm is a rational reconstruction of M5 with some
enhancements. M5Base. Implements base routines for generating M5 Model trees and rule
the original algorithm M5 was invented by R. Quinlan and Yong Wang. M5P (where the P stands for
‘prime’) generates M5 model trees using the M5' algorithm, which was introduced in Wang & Witten
(1997) and enhances the original M5 algorithm by Quinlan (1992). The output of the analysis is shown
below:
=== Run information ===
Scheme: weka.classifiers.trees.M5P -M 4.0
Relation: Copy of Data_Rudra-weka.filters.unsupervised.attribute.Remove-R1
Instances: 945
Attributes: 6
BROAD, CLAIMS, DOMC, PSC, TOTRES, LIQLB
Test mode: 10-fold cross-validation
6. === Cross-validation ===
=== Summary ===
Correlation coefficient 0.9882
Mean absolute error 3.412
Root mean squared error 5.4145
Relative absolute error 11.529 %
Root relative squared error 15.1993 %
Total Number of Instances 40
Ignored Class Unknown Instances 905
Interpretation of the Results:
Based on the data above M5 algorithm generates modular tree which is formed by 5 linear models (LM)
based on the initial values of Broad money in the economy which if less than equal to 153.045 then we
7. have to follow linear model 1 (LM 1) to estimate Liquidity in the economy. If BROAD> 153.045 we check
PSC and move down the tree and choosing corresponding models to get the Liquidity and finally GDP
values as shown in the figure above.
Linear Regression with Weka
The second technique is to conduct linear regression through Weka on the same data. When the
outcome, or class, is numeric and all the attributes are numeric, linear regression is a natural technique
to consider. In the previous technique we created five linear models from the same data; hence M5P’s
performance is slightly worse than any linear model. The idea is to express the class as a linear
combination of the attributes with predetermined weights. From the previous data, we can also find
linear regression equation between various parameters determining GDP. To run the regression, go to
classify tab on Weka and choose linear regression from functions as shown.
Figure 3 Shows where to find LR in Weka
Following output is generated by the above analysis:
=== Run information ===
Scheme: weka.classifiers.functions.LinearRegression -S 0 -R 1.0E-8
Relation: Copy of Data_Rudra
Instances: 945
Attributes: 7
YEAR
BROAD
8. CLAIMS
DOMC
PSC
TOTRES
LIQLB
Test mode: 10-fold cross-validation
=== Classifier model (full training set) ===
Linear Regression Model
LIQLB = 1.2523 * BROAD + 0.6062 * CLAIMS + -0.1407 * DOMC 0 * TOTRES + -6.9705
Time taken to build model: 0.2 seconds
=== Cross-validation ===
=== Summary ===
Correlation coefficient 0.9738
Mean absolute error 4.8731
Root mean squared error 8.0404
Relative absolute error 16.4661 %
Root relative squared error 22.5707 %
Total Number of Instances 40
Ignored Class Unknown Instances 905
The above analysis gives as a mathematical relationship (linear) between various variables. The Value of
the fifth variable (dependent) can be found out once other independent variable values are known. This
equation also tells how these variables are related. A negative relation shows reciprocal relationship and
vice-versa. To see the same relation is pictorial form simply goes to visualize tab on Weka explorer. The
same is shown in the figure below.
9. CLUSTERING IN WEKA
Clustering is a technique used to group similar instances or rows in term of Euclidean distance. We have
used SimpeKMeans clustering algorithm to analyze clustering in our initial data. In SimpleKMeans
implementation clustering data use k-means, or the algorithm can decide using cross-validation- in
which case number of folds is fixed at 10. The figure below shows the output of SimpeKMeans for the
above data. The result is shown as table with rows that are attributes names and columns that
correspond to cluster centroids; an additional cluster at the beginning shows the entire data set. The
number of instances in each cluster appears in parenthesis at the top of its column. Each table entry is
either the mean or mode of the corresponding attribute for the cluster in that column. The bottom of
the output shows the result of applying the learned cluster model. In this case, it assigned each training
set to one of the clusters, showing the same result as the parenthetical numbers at the top of each
column. An alternative is to use a separate test set or a percentage split of training data, in which case
figures would be different. This technique could be used with data from other countries in addition of
the present data that is taken for Japan.
10. === Run information ===
Scheme:weka.clusterers.SimpleKMeans -N 2 -A "weka.core.EuclideanDistance -R first-last" -I 500 -S 10
Relation: Copy of Data_Rudra
Instances: 945
Attributes: 7
YEAR
BROAD
CLAIMS
DOMC
PSC
TOTRES
LIQLB
Test mode:evaluate on training data
11. === Model and evaluation on training set ===kMeans======
Number of iterations: 5
Within cluster sum of squared errors: 12.988387913678944
Missing values globally replaced with mean/mode
Cluster centroids:
Cluster#
Attribute Full Data 0 1
(945) (929) (16)
=================================================================
YEAR 1989.5 1989.2933 2001.5
BROAD 174.1633 173.4625 214.8525
CLAIMS 6.6645 6.8103 -1.7981
DOMC 242.2808 241.2956 299.4794
PSC 168.2627 167.8077 194.685
TOTRES 248907476505.9463 243675387834.3592 552695625000
LIQLB 175.2342 174.7166 205.2875
Time taken to build model (full training data) : 0.14 seconds
=== Model and evaluation on training set ===
Clustered Instances
0 929 (98%)
1 16 (2%)
We can also visualize the clusters formed. Right click on the result-list output and select cluster visualize.
We get the following output: