KNN Classifier in Java

knn.java

    private String classify_accelerometer_sample (ArrayList<AccelerometerDataPoint> sample) {
        double mean = 0.0, variance = 0.0;
        int index_nearest_neighbour;

        // Compute the mean Z-axis value for the sample
        for (AccelerometerDataPoint d : sample) {
            mean = mean + d.getAz();
        }
        mean = mean / (double)acc_sample_window;


        // Compute the variance across the Z-axis values
        for (AccelerometerDataPoint d : sample) {
            variance = variance + ((d.getAz() - mean) * (d.getAz() - mean));
        }
        variance = variance / ((double)acc_sample_window - 1);


        // Create a sorted list of training points based on difference in variance
        ArrayList<AccelerometerTrainingPoint> sorted = new ArrayList<AccelerometerTrainingPoint>();

        // For all elements in the training points
        for (AccelerometerTrainingPoint p : this.acc_train_data) {

            // Find the smallest one
            index_nearest_neighbour = 0;

            for (int i = 0; i < this.acc_train_data.size(); ++i) {
                double candidate_variance    = this.acc_train_data.get(i).getZ_var();
                double current_variance      = this.acc_train_data.get(index_nearest_neighbour).getZ_var();

                double candidate_difference  = Math.abs(candidate_variance - variance);
                double current_difference    = Math.abs(current_variance - variance);

                if (candidate_difference < current_difference) {
                    index_nearest_neighbour = i;
                }
            }

            // Append it to the arraylist
            sorted.add(this.acc_train_data.get(index_nearest_neighbour));
        }

        // For the first K items training data points in the arraylist, count the number of walk/standing
        int walking = 0;
        int standing = 0;

        for (int i = 0; i < this.acc_k_size; ++i) {
            AccelerometerTrainingPoint p = sorted.get(i);
            if (p.getLabel() == 0) {
                walking++;
            } else {
                standing++;
            }
        }

        if (walking > standing) {
            return "walking";
        } else {
            return "standing";
        }
    }