data mining - Calculating entropies of attributes - Data Science …
Feb 12, 2015 · Can you please show the step by step calculation of Entropy(Ssun)? I do not understand how 0.918 is arrived at. I tried but I get the values as 0.521089678, 0.528771238, …
machine learning - Data Science Stack Exchange
Mar 4, 2022 · For example, Information gain comes from the concept of entropy, and Gini calculates the total variance of the Benoulli trials. but for this measure, I do not quite see what …
How Can I Compute Information-Gain for Continuous- Valued
Nov 18, 2017 · dataset data-mining predictive-modeling decision-trees convolutional-neural-network Share Improve this question edited Feb 13, 2021 at 19:21
python - How to apply entropy discretization to a dataset - Data ...
Oct 21, 2021 · I have a simple dataset that I'd like to apply entropy discretization to. The program needs to discretize an attribute based on the following criteria When either the condition “a” or …
machine learning - Data Science Stack Exchange
Feb 16, 2016 · Can someone practically explain the rationale behind Gini impurity vs Information gain (based on Entropy)? Which metric is better to use in different scenarios while using …
text mining - Feature Selection - Conditional Entropy - Data …
Sep 17, 2020 · 2 I've developed an algorithm to define conditional entropy for feature selection in text classification. I'm following the formula at Machine Learning from Text by Charu C. …
data mining - Gini coefficient vs Gini impurity - decision trees
Sep 10, 2014 · The problem refers to decision trees building. According to Wikipedia 'Gini coefficient' should not be confused with 'Gini impurity'. However both measures can be used …
machine learning - Data Science Stack Exchange
Jan 25, 2020 · I am trying to implement k-means clustering on 60-70 features and I came across a post for feature selection technique on quora by Julian Ramos, but I fail to understand few …
Decision Tree Induction using Information Gain and Entropy - Data ...
May 22, 2020 · I’m trying to build a decision tree algorithm, but I think I misinterpreted how information gain works. Let’s say we have a balanced classification problem. So, the initial …
machine learning - What is the meaning of the Gini Index? - Data ...
Sep 23, 2021 · I'm studying random forest models, but I don't understand what the Gini index is and what it's for. Does anyone have any material on this or can give me an explanation? Thanks!