numpy sklearn.decomposition.PCA

This function first applies PCA (Principal Component Analysis) to reduce the dimensions of the dataset, and then uses PermutationImportance to explain the importance of the principal components. PermutationImportance evaluates the importance of features by randomly shuffling feature values and observing the change in model performance.

The type of code 2024-12-16 12:16:44 14 views

eli5 sklearn

This function uses PermutationImportance from the eli5 library to evaluate the feature importance of a randomly selected sklearn model. It first selects a model, then fits PermutationImportance to the model, and finally returns the feature importance.

The type of code 2024-12-16 12:16:00 12 views

numpy pandas

This function generates a random walk using numpy, converts it to a DataFrame using pandas, and then fits a linear regression model from sklearn to the random walk. It returns the coefficient of the model, which can be used to evaluate the trend of the random walk.

Custom function 2024-12-16 12:15:57 12 views

numpy shap

This function uses the SHAP library to explain a given RandomForestClassifier model and data, returning SHAP values for each sample and feature.

Function 2024-12-16 12:14:41 8 views

pandas numpy

This function takes a pandas DataFrame as input, normalizes the numeric columns using StandardScaler from sklearn, and returns the original DataFrame with the normalized numeric columns concatenated.

Function 2024-12-16 12:13:22 7 views

numpy pandas

This function first generates a random dataset, then fits a RandomForestRegressor model to it, and then uses the SHAP library to interpret the model's predictions and generate SHAP values.

Function 2024-12-16 12:12:12 4 views

eli5 library

The function randomly selects a method from the eli5 library and demonstrates its usage with a dummy dataset and model.

The type of code 2024-12-16 12:11:48 3 views

Eli5 SKLearn

This code defines a function named random_eli5_function that randomly selects a function from the Eli5 library to explain a randomly generated RandomForestClassifier model. First, it randomly selects a function from the Eli5 library, then creates a random classification dataset and a RandomForestClassifier model. Next, it uses the selected function to explain the model.

The type of code 2024-12-16 12:11:10 20 views

Eli5 sklearn

This function uses the PermutationImportance class from the Eli5 library to calculate the feature importance of a given model on the data. It takes data, target, and model as inputs and returns the feature importance scores.

Python Function 2024-12-16 12:10:59 4 views

The code

This code first generates a random dataset, then trains a random forest classifier, and uses Eli5's PermutationImportance to calculate feature importances. Finally, it returns the mean importance of each feature.

The type of code 2024-12-16 12:10:44 6 views