python implement of random_forest

Jidong Li
python implement of random_forest
Average: 4.8 (4 votes)
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Naive implement of random_forest in python


Random Forest Workflow

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Workflow Description
The go to algorithm to utilize for multiclass classification problems is Random Forest, essentially an ensemble of decision trees with a random set of features for each tree. This leads to less bias and variance within the final decision accuracy.

Random Forest Walkthrough

Insight/Output Description

1. Exploratory data analysis like summary statistics, data visualization, data cleaning, encoding, standardizing/normalizing, imputation and deletion, PCA, feature selection

2. Binary Classification with both numeric and categorical variables

■ Logistic Regression

■ K Nearest Neighbor

■ Decision Tree

■ Random Forest

■ Naïve Bayes

■ Support Vector Machine

3. Gini index and Random Forest algorithm

4. Evaluation and Explanation

■ Performance metric: Accuracy, Recall, Precision, F1 score