简化，修复

luokn · Jul 21, 2021 · 8ee7f46 · 8ee7f46
1 parent db17836
commit 8ee7f46
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Showing 9 changed files with 18 additions and 18 deletions.
diff --git a/AdaBoost/adaboost.py b/AdaBoost/adaboost.py
@@ -72,7 +72,7 @@ def load_data():
     x, y = load_data()
     plt.figure(figsize=[12, 6])
     plt.subplot(1, 2, 1)
-    plt.title('Real')
+    plt.title('Truth')
     plt.scatter(x[0, :, 0], x[0, :, 1], color='r', marker='.')
     plt.scatter(x[1, :, 0], x[1, :, 1], color='g', marker='.')
 
@@ -85,7 +85,7 @@ def load_data():
 
     x0, x1 = x[pred == -1], x[pred == 1]
     plt.subplot(1, 2, 2)
-    plt.title('Pred')
+    plt.title('Prediction')
     plt.scatter(x0[:, 0], x0[:, 1], color='r', marker='.')
     plt.scatter(x1[:, 0], x1[:, 1], color='g', marker='.')
     plt.show()
diff --git a/GMM/gmm.py b/GMM/gmm.py
@@ -71,7 +71,7 @@ def load_data():
     x = load_data()
     plt.figure(figsize=[12, 6])
     plt.subplot(1, 2, 1)
-    plt.title('Real')
+    plt.title('Truth')
     plt.scatter(x[0, :, 0], x[0, :, 1], color='r', marker='.')
     plt.scatter(x[1, :, 0], x[1, :, 1], color='g', marker='.')
 
@@ -82,7 +82,7 @@ def load_data():
 
     x0, x1 = x[pred == 0], x[pred == 1]
     plt.subplot(1, 2, 2)
-    plt.title('Pred')
+    plt.title('Prediction')
     plt.scatter(x0[:, 0], x0[:, 1], color='r', marker='.')
     plt.scatter(x1[:, 0], x1[:, 1], color='g', marker='.')
     plt.show()
diff --git a/KMeans/kmeans.py b/KMeans/kmeans.py
@@ -52,7 +52,7 @@ def load_data():
     x = load_data()
     plt.figure(figsize=[12, 6])
     plt.subplot(1, 2, 1)
-    plt.title('Real')
+    plt.title('Truth')
     plt.scatter(x[0, :, 0], x[0, :, 1], color='r', marker='.')
     plt.scatter(x[1, :, 0], x[1, :, 1], color='g', marker='.')
     plt.scatter(x[2, :, 0], x[2, :, 1], color='b', marker='.')
@@ -64,7 +64,7 @@ def load_data():
 
     x0, x1, x2 = x[pred == 0], x[pred == 1], x[pred == 2]
     plt.subplot(1, 2, 2)
-    plt.title('Pred')
+    plt.title('Prediction')
     plt.scatter(x0[:, 0], x0[:, 1], color='r', marker='.')
     plt.scatter(x1[:, 0], x1[:, 1], color='g', marker='.')
     plt.scatter(x2[:, 0], x2[:, 1], color='b', marker='.')

diff --git a/KNN/knn.py b/KNN/knn.py
@@ -45,7 +45,7 @@ def load_data():
 
     plt.figure(figsize=[12, 6])
     plt.subplot(1, 2, 1)
-    plt.title('Real')
+    plt.title('Truth')
     plt.scatter(x[0, :, 0], x[0, :, 1], color='r', marker='.')
     plt.scatter(x[1, :, 0], x[1, :, 1], color='g', marker='.')
     plt.scatter(x[2, :, 0], x[2, :, 1], color='b', marker='.')
@@ -59,7 +59,7 @@ def load_data():
 
     x0, x1, x2 = x[pred == 0], x[pred == 1], x[pred == 2]
     plt.subplot(1, 2, 2)
-    plt.title('Pred')
+    plt.title('Prediction')
     plt.scatter(x0[:, 0], x0[:, 1], color='r', marker='.')
     plt.scatter(x1[:, 0], x1[:, 1], color='g', marker='.')
     plt.scatter(x2[:, 0], x2[:, 1], color='b', marker='.')

diff --git a/LDA/lda.py b/LDA/lda.py
@@ -4,8 +4,8 @@
 # @Email : olooook@outlook.com
 
 import numpy as np
-from numpy import linalg as LA
 from matplotlib import pyplot as plt
+from numpy import linalg as LA
 
 
 class LDA:
@@ -72,7 +72,7 @@ def load_data():
     x, y = load_data()
     plt.figure(figsize=[18, 6])
     plt.subplot(1, 3, 1)
-    plt.title('Real')
+    plt.title('Truth')
     plt.xlim(-5, 5)
     plt.ylim(-5, 5)
     plt.scatter(x[0, :, 0], x[0, :, 1], color='r', marker='.')

diff --git a/LogisticRegression/logistic_regression.py b/LogisticRegression/logistic_regression.py
@@ -59,7 +59,7 @@ def train_logistic_regression(model, x, y, epochs, batch_size=32):
     x, y = load_data()
     plt.figure(figsize=[12, 6])
     plt.subplot(1, 2, 1)
-    plt.title('Real')
+    plt.title('Truth')
     plt.xlim(-5, 5)
     plt.ylim(-5, 5)
     plt.scatter(x[0, :, 0], x[0, :, 1], color='r', marker='.')
@@ -74,7 +74,7 @@ def train_logistic_regression(model, x, y, epochs, batch_size=32):
 
     x0, x1 = x[pred == 0], x[pred == 1]
     plt.subplot(1, 2, 2)
-    plt.title('Pred')
+    plt.title('Prediction')
     plt.xlim(-5, 5)
     plt.ylim(-5, 5)
     plt.scatter(x0[:, 0], x0[:, 1], color='r', marker='.')

diff --git a/PCA/pca.py b/PCA/pca.py
@@ -42,7 +42,7 @@ def load_data():
     x0, x1, x2 = x.reshape(3, -1, 2)
     plt.figure(figsize=[15, 5])
     plt.subplot(1, 3, 1)
-    plt.title('Real')
+    plt.title('Truth')
     plt.xlim(-5, 5)
     plt.ylim(-5, 5)
     plt.scatter(x0[:, 0], x0[:, 1], color='r', marker='.')

diff --git a/Perceptron/perceptron.py b/Perceptron/perceptron.py
@@ -54,7 +54,7 @@ def train_perceptron(model, x, y, epochs):
     x, y = load_data()
     plt.figure(figsize=[12, 6])
     plt.subplot(1, 2, 1)
-    plt.title('Real')
+    plt.title('Truth')
     plt.xlim(-5, 5)
     plt.ylim(-5, 5)
     plt.scatter(x[0, :, 0], x[0, :, 1], color='r', marker='.')
@@ -69,7 +69,7 @@ def train_perceptron(model, x, y, epochs):
 
     x0, x1 = x[pred == -1], x[pred == 1]
     plt.subplot(1, 2, 2)
-    plt.title('Pred')
+    plt.title('Prediction')
     plt.xlim(-5, 5)
     plt.ylim(-5, 5)
     plt.scatter(x0[:, 0], x0[:, 1], color='r', marker='.')

diff --git a/SVM/svm.py b/SVM/svm.py
@@ -33,7 +33,7 @@ def __init__(self, C=1.0, kernel='linear', iterations=100, tol=1e-3, **kwargs):
 
     def fit(self, X: np.ndarray, Y: np.ndarray):
         self.X, self.Y = X, Y
-        self.alpha = np.ones([len(X)], dtype=np.float)  # 拉格朗日乘子
+        self.alpha = np.ones([len(X)])  # 拉格朗日乘子
         for _ in range(self.iterations):
             E = np.array([self._calc_error(i) for i in range(len(X))])  # 此次迭代缓存的误差
             for i1 in range(len(X)):  # 外层循环，寻找第一个alpha
@@ -134,7 +134,7 @@ def load_data():
     x, y = load_data()
     plt.figure(figsize=[18, 6])
     plt.subplot(1, 3, 1)
-    plt.title('Real')
+    plt.title('Truth')
     plt.xlim(-7, 7)
     plt.ylim(-7, 7)
     plt.scatter(x[0, :, 0], x[0, :, 1], color='r', marker='.')
@@ -149,7 +149,7 @@ def load_data():
 
     x0, x1 = x[pred == -1], x[pred == 1]
     plt.subplot(1, 3, 2)
-    plt.title('Pred')
+    plt.title('Prediction')
     plt.xlim(-7, 7)
     plt.ylim(-7, 7)
     plt.scatter(x0[:, 0], x0[:, 1], color='r', marker='.')