python implement of random_forest


jli807
python implement of random_forest
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Average: 4.8 (4 votes)
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1
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Project Type
Project Description

Naive implement of random_forest in python

Data
Workflow

Random Forest Workflow

alicia
Upload Workflow
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.
Insights/Outputs

Random Forest Walkthrough

alicia
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