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authorVasil Zlatanov <v@skozl.com>2019-02-04 19:04:09 +0000
committerVasil Zlatanov <v@skozl.com>2019-02-04 19:04:09 +0000
commitc12c70bbb6ccf15d06a6ee7888642942f4fb8d83 (patch)
tree559eb4cdfcd730ac0f8b66b408aabcea08fdcd03
parentd248ef0e0c9c9e7b924c3508f43e339687975627 (diff)
downloade4-vision-c12c70bbb6ccf15d06a6ee7888642942f4fb8d83.tar.gz
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Use correct estimator size
-rwxr-xr-xevaluate.py6
1 files changed, 2 insertions, 4 deletions
diff --git a/evaluate.py b/evaluate.py
index 92c4107..2de8f8c 100755
--- a/evaluate.py
+++ b/evaluate.py
@@ -7,9 +7,9 @@ CLUSTER_CNT = 256
KMEANS = False
if KMEANS:
- N_ESTIMATORS = 1000
-else:
N_ESTIMATORS = 1
+else:
+ N_ESTIMATORS = 100
import numpy as np
import matplotlib.pyplot as plt
@@ -38,13 +38,11 @@ def make_histogram(data):
histogram = np.zeros((data.shape[0], data.shape[1],CLUSTER_CNT*N_ESTIMATORS))
for i in range(data.shape[0]):
for j in range(data.shape[1]):
- print(data[i][j].shape)
if (KMEANS):
histogram[i][j] = np.bincount(kmeans.predict(data[i][j].T),minlength=CLUSTER_CNT)
else:
leaves = trees.apply(data[i][j].T)
leaves = np.apply_along_axis(np.bincount, axis=0, arr=leaves, minlength=CLUSTER_CNT)
- print(leaves.shape)
histogram[i][j] = leaves.reshape(CLUSTER_CNT*N_ESTIMATORS)
return histogram