27 Great Resources About Decision Trees

27 Great Resources About Decision Trees

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, correlation, outliers, regression, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, time series, cross-validation, model fitting, dataviz, AI and many more. To keep receiving these articles, sign up on DSC.
27 Great Resources About Decision Trees

Customer Churn – Logistic Regression with R 
Predicting Flights Delay Using Supervised Learning, Logistic Regression 
Logistic Regression vs Decision Trees vs SVM: Part II 
Logistic Regression Vs Decision Trees Vs SVM: Part I 
Making data science accessible – Logistic Regression 
Logistic Regression using python 
Logistic Regression and Maximum Entropy explained with examples 
Decision tree vs Logistic Regression 
Excluding variables from a logistic regression model based on correlation 
Regression, Logistic Regression and Maximum Entropy +
Oversampling/Undersampling in Logistic Regression 
Fraud Detection using logistic regression 
Explaining variability in logistic regression 
Handling Imbalanced data when building regression models 
Multiple logistic Regression Power Analysis 
Model Accuracy – In logistic Regression 
Outliers in Logistic Regression 
Logistic Regression – Hosmer Lemeshow test 
Logistic regression intercept term not significant 
Cut off point in logistic regression 
Techniques to address very low event rate for Logistic Regression Model 
The best kept secret about linear and logistic regression 
Hidden Decision Trees vs. Decision Trees or Logistic Regression 
Logistic regression on large imbalance datasets 
Multinomial Logistic Regression Predicting Cluster Membership 
Introduction to Logistic Regression with R 
Logistic Regression – General concepts 

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