Go Machine Learning Projects

Putting it all together

Now we have all the pieces. Let's look at how to put it all together:

1. We first ingest the dataset and then split the data out into training and cross validation sets. The dataset is split into ten parts for a k-fold cross-validation. We won't do that. Instead, we'll do a single fold cross-validation by holding out 30% of the data for cross-validation:

  typ := "bare"  examples, err := ingest(typ)  log.Printf("errs %v", err)  log.Printf("Examples loaded: %d", len(examples))  shuffle(examples)  cvStart := len(examples) - len(examples)/3  cv := examples[cvStart:]  examples = examples[:cvStart]

2. We then train the classifier and then check to see whether the classifier can predict its own dataset well:

  c := New() c.Train(examples) ...