From 19373e897dcbf3c71b878864a3d1c40c8dff2a7a Mon Sep 17 00:00:00 2001
From: BaptisteBrd <75663738+BaptisteBrd@users.noreply.github.com>
Date: Fri, 10 Nov 2023 17:33:00 +0100
Subject: [PATCH] exchange data test and train
---
knn.py | 23 +++++++++++++++--------
1 file changed, 15 insertions(+), 8 deletions(-)
diff --git a/knn.py b/knn.py
index 2833ea7..9e44028 100644
--- a/knn.py
+++ b/knn.py
@@ -2,11 +2,16 @@ import numpy as np
import read_cifar
import matplotlib.pyplot as plt
-def distance_matrix(a,b):
- sum_a = np.sum(a**2, axis=1, keepdims=True)
- sum_b = np.sum(b**2, axis=1, keepdims=True)
- dist = np.sqrt(-2 * a.dot(b.T) + sum_a + sum_b)
- return dist
+def distance_matrix(A,B):
+
+ sum_of_squares_A = np.sum(A**2, axis=1,keepdims=True)
+ sum_of_squares_B = np.sum(B**2, axis=1,keepdims=True).T
+ dot_product = np.dot(A, B.T)
+
+
+ dists=np.sqrt(sum_of_squares_A+sum_of_squares_B-2*dot_product)
+
+ return dists
@@ -30,8 +35,10 @@ def knn_predict(dists, labels_train, k):
def evaluate_knn(data_train, labels_train, data_test, labels_test, k):
rate = 0
- dist_train_test = distance_matrix(data_train, data_test)
+ dist_train_test = distance_matrix(data_test, data_train)
prediction = knn_predict(dist_train_test, labels_train, k)
+ print(len(prediction))
+ print(len(labels_test))
for j in range(len(prediction)):
if prediction[j]==labels_test[j]:
rate +=1
@@ -46,6 +53,7 @@ def knn_final():
data_train_f, labels_train_f, data_test_f, labels_test_f = read_cifar.split_dataset(data, labels, 0.9)
for k in range_k :
+ print(k)
rate_k = evaluate_knn(data_train_f, labels_train_f, data_test_f, labels_test_f, k)
rates.append(rate_k)
@@ -67,5 +75,4 @@ if __name__ == "__main__" :
knn_final()
#a1 = np.array([[0,0,1],[0,0,0],[1,1,2]])
#b1 = np.array([[1,3,1], [1,1,4], [1,5,1]])
- #print(distance_matrix(a1,b1))
-
+ #print(distance_matrix(a1,b1))
\ No newline at end of file
--
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