From 97acdd6ea9e378c90cf9a199e746ebca59a4d5e6 Mon Sep 17 00:00:00 2001 From: Vasil Zlatanov Date: Mon, 11 Feb 2019 17:47:09 +0000 Subject: Add histogram fig --- evaluate.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) (limited to 'evaluate.py') diff --git a/evaluate.py b/evaluate.py index dff8482..9cb5f78 100755 --- a/evaluate.py +++ b/evaluate.py @@ -19,7 +19,7 @@ import time parser = argparse.ArgumentParser() parser.add_argument("-d", "--data", help="Data path", action='store_true', default='data.npz') parser.add_argument("-c", "--conf_mat", help="Show visual confusion matrix", action='store_true') -parser.add_argument("-k", "--kmean", help="Perform kmean clustering with --kmean cluster centers", type=int, default=0) +parser.add_argument("-k", "--kmean", help="Perform kmean clustering with KMEAN cluster centers", type=int, default=0) parser.add_argument("-l", "--leaves", help="Maximum leaf nodes for RF classifier", type=int, default=256) parser.add_argument("-e", "--estimators", help="number of estimators to be used", type=int, default=100) parser.add_argument("-D", "--treedepth", help="depth of trees", type=int, default=5) @@ -49,6 +49,11 @@ def make_histogram(data, model, args): leaves = model.apply(data[i][j].T) leaves = np.apply_along_axis(np.bincount, axis=0, arr=leaves, minlength=args.leaves) histogram[i][j] = leaves.reshape(hist_size) + + print(histogram[0][0].shape) + plt.bar(np.arange(100), histogram[0][0].flatten()) + plt.show() + return histogram def run_model (data, train, test, train_part, args): -- cgit v1.2.3-70-g09d2