Machine-Learning

This library is made to simplify the use of regression on machine learning

Technologies

• jblas-1.2.4
• java 8

Installation

At the moment, there is only one way available to use the API.

From the source code

You can build the project from the source in this repository, export as a JAR file and Add to the Build Path of your project.

API Overview

  // Here, we load the data necessary to train the model.
  DoubleMatrix dataset = LoadData.load("train_data/data_1.txt", ",");
  
  // split the data in two: features and expected answers for each set of features(row)
  DoubleMatrix X = dataset.getColumn(0);
  DoubleMatrix Y = dataset.getColumn(1);
		
  /*define the model to use. Obs: first parameter is the learning coeficient, 
   *second parameter is the number of iterations to      
   *train the model e finally the last parameter is a question "Do you    want to normalize the data?".
   */
   Regression model = new LinearRegression(0.01, 2000, false);
   model.train(X, Y);
   

  // After training the model we predict some values, just to test the model
  DoubleMatrix predict1 = model.predict(new DoubleMatrix(new double[] {3.5}));
  DoubleMatrix predict2 = model.predict(new DoubleMatrix(new double[] {7}));
  
  System.out.println("For population = 35,000, we predict a profit of " + (predict1.get(0) * 10000));
  System.out.println("For population = 70,000, we predict a profit of " + (predict2.get(0) * 10000));
  ```