hal.ml package


hal.ml.correlation module

Correlate values in arrays producing fancy good-looking matrices

class hal.ml.correlation.CorrelationMatrix(title, headers_to_test, headers, data)[source]

Bases: object

Common operations for a correlation matrix

static get_correlation_matrix(matrix)[source]

Finds correlation matrix of matrix

Parameters:matrix – List of features to get correlation matrix
Returns:correlation matrix

Computes correlation matrix of columns :return: Correlation matrix of columns

static save_correlation_matrix_from_folder(folder_path)[source]

Saves each file’s correlation matrix of common headers

Parameters:folder_path – Folder containing logs data

Saves correlation matrix of selected headers

Parameters:out_file – Output file

Shows the given correlation matrix as image

Parameters:correlation_matrix – Correlation matrix of features

Shows the correlation matrix of columns

hal.ml.features module

Collection of methods to find weights of features and select the best ones

class hal.ml.features.FeatureSelect(x, y)[source]

Bases: object

Selects best features


Finds the optimal number of features :return: optimal number of features and ranking


Selects k best features in dataset

Parameters:k – features to select
Returns:k best features

hal.ml.predict module

General model to make prediction about everything

class hal.ml.predict.BasePrediction(model, rounds)[source]

Bases: object

The mother of all predictions

train(x_data, y_data)[source]

Trains model on inputs

  • x_data – x matrix
  • y_data – y array