gnb_9.kt

// Class to implement Gaussian Naive Bayes
class GaussianNB( private var dataFrame : DataFrame ) {

    // Array to store Gaussian Distributions for each feature.
    private var featureDistributions : Array<GaussianDistribution>

    // Prior probabilities stored in a HashMap of form ( column_name , prior_prob )
    private var priorProbabilities : HashMap<String,Float>

    private var resultCallback : ResultCallback? = null

    init {

        // Construct Gaussian Distributions for each feature and append them to `featureDistributions`.
        val GDs = ArrayList<GaussianDistribution>()
        for ( featureColumn in dataFrame.featureColumns ) {
            GDs.add( GaussianDistribution( featureColumn.featureMean , featureColumn.featureStdDev ))
        }
        featureDistributions = GDs.toTypedArray()

        // Compute prior probabilities and store them in `priorProbabilities`.
        priorProbabilities = computePriorProbabilities( dataFrame.labels )

    }