Market analysis using Santander data set.

1. Final Project
Market Analysis
Amin Rashidi, Nishtha Adroja, Fangning He
INFO 7390 – Advances in Data Science

2. The Flow
Data Exploration
•Create charts and dashboard in tableau to do data exploration
Build Prediction
Model
• Dividing the dadaset into training and testing datasets.
•Training a model by using Decision Tree, Random Forest and Deep Belif Netwok
•Train the best model for each algorithm with all the data
•Save all the models to R objects and make ready for Azure
Azure Project
•Creating the model in Azure.
•Deploying the web serivce.
•Generateing the output based on the input data.
Web Applicaton
•creating the front-end using C# and asp.net

3. Data Exploration
• Number of features: 370
• Number of samples: 76020

4. Model Training
How to deal with unbalanced datasets
 It results in a highly biased mode ageist unsatisfied class
 Solution:
 Under-sampling
 Cost Sensitive Learning

5. Model Training
Variable Selection

6. Model Training
The models
 We eventually selected 6 variable
 Trained using
 Decision Tree
 Random Forest
 Deep Belief Network
Layer 1 Layer 2 Layer 3 Batch
Size
Learning
Rate
Accuracy Kappa
50 200 200 5 0.1 0.674629 0.350697
200 50 50 5 0.1 0.673806 0.349025
200 200 50 2 0.1 0.672982 0.347466
50 50 50 5 0.1 0.672982 0.347352
200 50 50 5 0.8 0.672982 0.347296
50 200 50 5 0.1 0.672982 0.347296
200 50 50 2 0.4 0.672158 0.345567
200 50 200 2 0.1 0.672158 0.34551
50 50 50 5 0.4 0.672158 0.34534
Model Name Accuracy Kappa Kappa (with all variables)
Random Forest 0.76 0.17 0.17
Decision Tree 0.40 0.04 0.06
DBN 0.61 0.04 0.09

7. The Azure Machine Learning
 Web service input and model.zip are
connected to the same node to Execute R
Script.
 Enter Data Manually is connected to another
node to Execute R Script, and they are all
input data.
 Web service output is connected to the
output node of Execute R Script as the
output data.

8. Clients
1. Using ASP.NET and C#
 Web Application with Visual Studio
 Add API key and URL from Azure to
make connections
https://docs.microsoft.com/en-us/azure/app-service-web/media/web-sites-dotnet-get-started/create_app.png

9. Output : Web Application from Visual Studio

10. Output : Web Application from Visual Studio

11. Contribution Pie Chart
40.00%
40.00…
20.00…
Contribution
Amin Nishtha Fangning
Amin:
• Cleansing of data set
• Training and testing the data set
• Creating model objects for azure machine
learning
Nishtha/Alex:
• Data exploration using tableau
• Creating azure machine learning
• Creating web application using c# and
asp.net using visual studio and deploying the
web services
• Create report

12. Demo
 http://team2santanderbank.azurewebsites.net/