Scala: Guide for Data Science Professionals

Towards re-usable code

In the previous section, we performed all of the computation in a single script. While this is fine for data exploration, it means that we cannot reuse the logistic regression code that we have built. In this section, we will start the construction of a machine learning library that you can reuse across different projects.

We will factor the logistic regression algorithm out into its own class. We construct a LogisticRegression class:

import breeze.linalg._
import breeze.numerics._
import breeze.optimize._

class LogisticRegression(
    val training:DenseMatrix[Double], 
    val target:DenseVector[Double])
{

The class takes, as input, a matrix representing the training set and a vector denoting the target variable. Notice how we assign ...