hi-lasso-spark 1.0.0

High-Demensional LASSO_spark

Hi-LASSO_spark

Hi-LASSO_Spark(High-Demensinal LASSO Spark) is to improve the LASSO solutions for extremely high-dimensional data using pyspark. PySpark is the Python API written in python to support Apache Spark. Apache Spark is a distributed framework that can handle Big Data analysis. Spark is basically a computational engine, that works with huge sets of data by processing them in parallel and batch systems.

Installation

Hi-LASSO_Spark support Python 3.6+, Additionally, you will need numpy, scipy, and glmnet.

Hi-LASSO_spark is available through PyPI and can easily be installed with a pip install::

pip install hi_lasso_spark

Documentation

Read the documentation on readthedocs

Quick Start

# Data load
import pandas as pd
X = pd.read_csv('simulation_data_x.csv')
y = pd.read_csv('simulation_data_y.csv')

# General Usage
from hi_lasso_spark.Hi_LASSO_spark import HiLASSO_Spark

# Create a HiLasso model
model = HiLASSO_Spark(X, y, alpha=0.05, q1='auto', q2='auto', L=30, cv=5, node='auto', logistic=False)

# Fit the model
model.fit()

# Show the coefficients
model.coef_

# Show the p-values
model.p_values_

# Show the selected variable
model.selected_var_