Data Preparation for ML

Learn how to prepare data for machine learning in VSL.

What You'll Learn

• Creating Data objects
• Splitting data
• Feature engineering
• Data normalization

Creating Data

import vsl.ml

x_matrix := [][]f64{}  // Assume populated
y_vector := []f64{}    // Assume populated
mut data := ml.Data.from_raw_xy_sep(x_matrix, y_vector)!

Splitting Data

import vsl.ml

mut data := ml.Data.from_raw_xy_sep([][]f64{}, []f64{})!  // Assume populated
mut train_data, test_data := data.split(0.8)!
println('Training samples: ${train_data.nb_samples}')
println('Test samples: ${test_data.nb_samples}')

Next Steps

• Clustering
• Examples - Working examples