eli5 scikit-learn

This function creates a randomly chosen machine learning pipeline using CountVectorizer for text vectorization and LogisticRegression or DecisionTreeClassifier as the classifier. Then, it uses the show_weights function from the eli5 library to generate a feature importances table and formats it as an HTML table.

Machine learning 2024-12-16 12:16:48 24 views

The code

This code defines a function that uses the SHAP library to analyze the interpretability of a machine learning model. It accepts a trained model and input data, computes SHAP values, and visualizes them using waterfall plots.

The type of code 2024-12-16 12:16:05 13 views

The code

The code uses the LightGBM library to extract feature importance from a trained model. It also uses NumPy for numerical operations.

The type of code 2024-12-16 12:15:48 10 views

Autobahn Twisted

This code defines a WebSocket server using the Autobahn library. The server listens on port 8080 of the local machine, accepts connections and messages from clients, and echoes received messages back to the clients.

WebSocket Server 2024-12-16 12:15:16 11 views

Packages and

PermutationImportance, Explain_weights, Explainer, FeatureImportances

The type of code 2024-12-16 12:14:38 10 views

SHAP library

This function uses the SHAP library to generate a feature importance plot for a specified feature. It first creates a SHAP explainer, then computes the SHAP values for the feature, and displays these values using a waterfall plot.

The type of code 2024-12-16 12:14:02 10 views

Fairseq PyTorch

This function uses the Fairseq library to perform machine translation. It takes an input sentence and source and target languages, and then returns the translated sentence.

Machine translation 2024-12-16 12:13:47 26 views

Scikit-learn machine

This function uses a random forest classifier to classify the given data and returns the accuracy of the classification.

The type of code 2024-12-16 12:11:38 3 views

boto3 S3

This function randomly selects an object from a specified S3 bucket and downloads it to the local machine. It first lists all objects in the bucket, then randomly selects an object, and finally downloads it locally using boto3's download_file method.

The type of code 2024-12-16 12:11:26 21 views

XGBoost NumPy

This function generates a machine learning model using the XGBoost library by randomly selecting parameters such as learning rate, max depth, min child weight, and subsample ratio. The function accepts feature matrix X and label vector y as inputs and returns the trained XGBoost model.

Function 2024-12-16 12:05:07 7 views