Decision tree
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The document discusses decision trees, including: 1) What are decision trees and how they work by recursively splitting datasets into purer subsets based on features and thresholds. 2) The CART algorithm, which stands for Classification and Regression Trees and is the algorithm used in scikit-learn. 3) How to prevent overfitting with hyperparameters like minimum sample sizes and maximum depth when building decision trees.
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Understanding Deep Learning Requires Rethinking Generalization
Understanding Deep Learning Requires Rethinking Generalization
Recently uploaded
Generative AI Use cases applications solutions and implementation.pdf
Generative AI solutions encompass a range of capabilities from content creation to complex problem-solving across industries. Implementing generative AI involves identifying specific business needs, developing tailored AI models using techniques like GANs and VAEs, and integrating these models into existing workflows. Data quality and continuous model refinement are crucial for effective implementation. Businesses must also consider ethical implications and ensure transparency in AI decision-making. Generative AI's implementation aims to enhance efficiency, creativity, and innovation by leveraging autonomous generation and sophisticated learning algorithms to meet diverse business challenges.
https://www.leewayhertz.com/generative-ai-use-cases-and-applications/
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
CalArts毕业证学历书【微信95270640】CalArts毕业证’圣力嘉学院毕业证《Q微信95270640》办理CalArts毕业证√文凭学历制作{CalArts文凭}购买学历学位证书本科硕士,CalArts毕业证学历学位证【实体公司】办毕业证、成绩单、学历认证、学位证、文凭认证、办留信网认证、（网上可查，实体公司，专业可靠）
(诚招代理)办理国外高校毕业证成绩单文凭学位证,真实使馆公证（留学回国人员证明）真实留信网认证国外学历学位认证雅思代考国外学校代申请名校保录开请假条改GPA改成绩ID卡
1.高仿业务:【本科硕士】毕业证,成绩单（GPA修改）,学历认证（教育部认证）,大学Offer,,ID,留信认证,使馆认证,雅思,语言证书等高仿类证书；
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（详情请加一下 文凭顾问+微信:95270640）欢迎咨询！子小伍玩小伍比山娃小一岁虎头虎脑的很霸气父亲让山娃跟小伍去夏令营听课山娃很高兴夏令营就设在附近一所小学山娃发现那所小学比自己的学校更大更美操场上还铺有塑胶跑道呢里面很多小朋友一班一班的快快乐乐原来城里娃都藏这儿来了怪不得平时见不到他们山娃恍然大悟起来吹拉弹唱琴棋书画山娃都不懂却什么都想学山娃怨自己太笨什么都不会斟酌再三山娃终于选定了学美术当听说每月要交元时父亲犹豫了山娃也说爸算了吧咱学校一学期才转
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 08 Doors and Windows.pdf
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 08 Doors and Windows
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Null Bangalore | Pentesters Approach to AWS IAM
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样
原件一模一样【微信：bwp0011】《(Humboldt毕业证书)柏林大学毕业证学位证》【微信：bwp0011】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
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四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
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◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
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8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
VARIABLE FREQUENCY DRIVE. VFDs are widely used in industrial applications for...
Variable frequency drive .A Variable Frequency Drive (VFD) is an electronic device used to control the speed and torque of an electric motor by varying the frequency and voltage of its power supply. VFDs are widely used in industrial applications for motor control, providing significant energy savings and precise motor operation.
Digital Twins Computer Networking Paper Presentation.pptx
A Digital Twin in computer networking is a virtual representation of a physical network, used to simulate, analyze, and optimize network performance and reliability. It leverages real-time data to enhance network management, predict issues, and improve decision-making processes.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Data Driven Maintenance | UReason Webinar
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
Computational Engineering IITH Presentation
This Presentation will give you a brief idea about what Computational Engineering at IIT Hyderabad has to offer.
SCALING OF MOS CIRCUITS m .pptx
this ppt explains about scaling parameters of the mosfet it is basically vlsi subject
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
Mechanical Engineering on AAI Summer Training Report-003.pdf
Mechanical Engineering PROJECT REPORT ON SUMMER VOCATIONAL TRAINING
AT MBB AIRPORT
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
Gas agency management system project report.pdf
The project entitled "Gas Agency" is done to make the manual process easier by making it a computerized system for billing and maintaining stock. The Gas Agencies get the order request through phone calls or by personal from their customers and deliver the gas cylinders to their address based on their demand and previous delivery date. This process is made computerized and the customer's name, address and stock details are stored in a database. Based on this the billing for a customer is made simple and easier, since a customer order for gas can be accepted only after completing a certain period from the previous delivery. This can be calculated and billed easily through this. There are two types of delivery like domestic purpose use delivery and commercial purpose use delivery. The bill rate and capacity differs for both. This can be easily maintained and charged accordingly.
Recently uploaded (20)
Generative AI Use cases applications solutions and implementation.pdf
Generative AI Use cases applications solutions and implementation.pdf
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 08 Doors and Windows.pdf
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 08 Doors and Windows.pdf
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
1FIDIC-CONSTRUCTION-CONTRACT-2ND-ED-2017-RED-BOOK.pdf
1FIDIC-CONSTRUCTION-CONTRACT-2ND-ED-2017-RED-BOOK.pdf
VARIABLE FREQUENCY DRIVE. VFDs are widely used in industrial applications for...
VARIABLE FREQUENCY DRIVE. VFDs are widely used in industrial applications for...
Digital Twins Computer Networking Paper Presentation.pptx
Digital Twins Computer Networking Paper Presentation.pptx
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...
Mechanical Engineering on AAI Summer Training Report-003.pdf
Mechanical Engineering on AAI Summer Training Report-003.pdf
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
Decision tree
- 1. Decision Tree Hands On Machine Learning with Scikit Learn and TensorFlow Matsuda laboratory B4 Wataru Hirota
- 2. Topics Today’s topic is.. • What is Decision Tree? • CART Algorithm • Regulate tree • Decision Tree for Regression • Experiment and Conclusion
- 3. Topics Today’s topic is.. • What is Decision Tree? • CART Algorithm • Regulate tree • Decision Tree for Regression • Experiment and Conclusion
- 4. What is Decision Tree? setosa (petal length) <= 2.45 (petal width) <= 1.75 versicolor virginica an iris whose • petal length is 2.8 • petal width is 1.6
- 5. What is Decision Tree? setosa (petal length) <= 2.45 (petal width) <= 1.75 versicolor virginica an iris whose • petal length is 2.8 • petal width is 1.6 is predicted as versicolor.
- 6. Merits of Decision Tree • easy to interpret (white box) • cf. Random Forest, Neural Network • effective learning with a small training data • very few assumptions about the training data (nonparametric)
- 7. Topics Today’s topic is.. • What is Decision Tree? • CART Algorithm • Regulate tree • Decision Tree for Regression • Experiment and Conclusion
- 8. What is CART? • Classification And Regression Tree • The algorithm used in scikit-learn. • Split the dataset in the two purest subsets recursively.
- 9. Definition Of Impurity 1. Gini index (default in scikit-learn) • 𝐺 = 1 − ∑ 𝑝( )* (+, • Slightly faster to computer 2. Entropy • 𝐻 = − ∑ 𝑝( log ( 𝑝()* (+, • Produce slightly more balanced tree
- 10. Cost Function of CART 𝐽 𝑘, 𝑡( = 𝑚89:; 𝑚 𝐼89:; + 𝑚>?@A; 𝑚 𝐼>?@A; (the cost is low ⟺ the split is good) • 𝑘 is the feature used to split. • 𝑡( is the threshold. • 𝑚 is the number of instances. • 𝐼 is the impurity of the set.
- 11. Algorithm of CART 1. Split the trainset based on the cost function. 2. Split the two sets generated recursively.
- 13. Topics Today’s topic is.. • What is Decision Tree? • CART Algorithm • Regulate tree • Decision Tree for Regression • Experiment and Conclusion
- 14. Need to Regulate • Decision Tree is likely to overfit! ○ ×
- 15. Hyper Parameters to Prevent Overfitting • min_sample_split • min_sample_leaf • max_leaf_nodes … and more (For more details see scikit-learn document.)
- 16. Topics Today’s topic is.. • What is Decision Tree? • CART Algorithm • Regulate tree • Decision Tree for Regression • Experiment and Conclusion
- 17. Basically same as classifier. Differences • Use the cost function as MSE. • Predicted value is the average of samples’ values in the node. Decision Tree for Regression
- 19. Topics Today’s topic is.. • What is Decision Tree? • CART Algorithm • Regulate tree • Decision Tree for Regression • Experiment and Conclusion
- 20. Experiment • Predict whether cancer will return or won’t. • Conditions • Train set is GSE_characters.xlms • The number of samples is about 2,000. • Set no hyper parameters.
- 21. Experiment 0 0.2 0.4 0.6 0.8 1 A G A,G G,T T,A G,A,T G, A, T, H Substitution Precision A … AGE G … Grade of cancer T … Tumor size H … HER2
- 23. Experiment • Set max_depth to simplify the model. • Used all features (A, G, T, H) . max_depth precision 3 0.7377 4 0.7363 5 0.7251 Generated Tree (max_depth=3)Estimated Generalization Precision
- 24. Conclusion • Decision Tree is a strong method applicable both for classification and regression. • Decision Tree is easy to interpret. • Overfitting is preventable with some hyper parameters (which are also interpretable) .