cd build
cmake ../
make -j4

 * @param(int) nEstimators The number of trees in the forest. Default: 10
 * @param(string) criterion The function to measure the quality of a split.
 * Supported criteria are “gini” for the Gini impurity and “entropy” for
 * the information gain. Default: gini
 * @param(string) maxFeatures
 *          * If “auto”, then max_features=sqrt(n_features).
 *          * If “sqrt”, then max_features=sqrt(n_features) (same as “auto”).
 *          * If “log2”, then max_features=log2(n_features).
 *          * If "None", then max_features=n_features.
 * Default: "log2"
 * @param(int) maxDepth The maximum depth of the tree. -1 means any depth. Default: -1
 * @param(int) minSamplesSplit The minimum number of samples required to split
 * an internal node. Default:2
 * @param(int) minSamplesLeaf The minimum number of samples required to be at
 * a leaf node. Default:1
 * @param(int) nJobs The number of jobs to run in parallel for both fit and
 * predict. Default:1

auto results = randomForest.predictProba(testData);
writeDataToCSV(results, testData, "../results/trainResults.csv", false);