TypeError: only integer scalar arrays can be converted to a scalar index , while trying kfold cv
TypeError: only integer scalar arrays can be converted to a scalar index , while trying kfold cv
尝试对包含 279 个文件的数据集执行 Kfold cv，执行 k-means 后文件的形状为 ( 279 , 5 , 90)。我重塑了它以使其适合 svm。现在形状是 ( 279, 5*90 )。尝试 Kfold cv 方法给我错误
"TypeError: only integer scalar arrays can be converted to a scalar
index "
#input
with open("dataset.pkl", "rb") as file:
dataset = pkl.load(file)
print(len(dataset))
x = [i[0] for i in dataset] #k-means cc
y = [i[1] for i in dataset] #label for the data
X = np.reshape(x,[279,5*90])
#cv
from sklearn.model_selection import KFold
kf = KFold(n_splits=5,random_state=42)
kf.get_n_splits(X)
for train_index, test_index in kf.split(X):
print("TRAIN:", train_index,"\n TEST:", test_index)
X_train, X_test, y_train, y_test = X[train_index], X[test_index],
y[train_index], y[test_index] #this is where i'm getting the error.
出来
TRAIN: [ 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73
74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91
92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109
110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127
128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145
146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163
164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181
182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199
200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217
218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235
236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253
254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271
272 273 274 275 276 277 278]
TEST: [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
48 49 50 51 52 53 54 55]
----------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-923-a534f873feb4> in <module>
2 for train_index, test_index in kf.split(X):
3 print("TRAIN:", train_index,"\n TEST:", test_index)
----> 4 X_train, X_test, y_train, y_test = X[train_index], X[test_index], y[train_index], y[test_index]
TypeError: only integer scalar arrays can be converted to a scalar index
y 是一个列表，不能像 numpy 数组一样被索引。
示例：
y = [1,2,3,4,6]
idx = np.array([0,1])
print (y[idx]) # This will throw an error as list cannot be index this way
print (np.array(y)[idx]) # This is fine because it is a numpy array now
解决方案
如果 y 是平面列表，则首先将其转换为 numpy
y = np.array([i[1] for i in dataset]) #label for the data
如果 y 是嵌套列表，则
y = np.array([np.array(i[1]) for i in dataset]) #label for the data
尝试对包含 279 个文件的数据集执行 Kfold cv，执行 k-means 后文件的形状为 ( 279 , 5 , 90)。我重塑了它以使其适合 svm。现在形状是 ( 279, 5*90 )。尝试 Kfold cv 方法给我错误
"TypeError: only integer scalar arrays can be converted to a scalar index "
#input
with open("dataset.pkl", "rb") as file:
dataset = pkl.load(file)
print(len(dataset))
x = [i[0] for i in dataset] #k-means cc
y = [i[1] for i in dataset] #label for the data
X = np.reshape(x,[279,5*90])
#cv
from sklearn.model_selection import KFold
kf = KFold(n_splits=5,random_state=42)
kf.get_n_splits(X)
for train_index, test_index in kf.split(X):
print("TRAIN:", train_index,"\n TEST:", test_index)
X_train, X_test, y_train, y_test = X[train_index], X[test_index],
y[train_index], y[test_index] #this is where i'm getting the error.
出来
TRAIN: [ 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73
74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91
92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109
110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127
128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145
146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163
164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181
182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199
200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217
218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235
236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253
254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271
272 273 274 275 276 277 278]
TEST: [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
48 49 50 51 52 53 54 55]
----------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-923-a534f873feb4> in <module>
2 for train_index, test_index in kf.split(X):
3 print("TRAIN:", train_index,"\n TEST:", test_index)
----> 4 X_train, X_test, y_train, y_test = X[train_index], X[test_index], y[train_index], y[test_index]
TypeError: only integer scalar arrays can be converted to a scalar index
y 是一个列表，不能像 numpy 数组一样被索引。
示例：
y = [1,2,3,4,6]
idx = np.array([0,1])
print (y[idx]) # This will throw an error as list cannot be index this way
print (np.array(y)[idx]) # This is fine because it is a numpy array now
解决方案
如果 y 是平面列表，则首先将其转换为 numpy
y = np.array([i[1] for i in dataset]) #label for the data
如果 y 是嵌套列表，则
y = np.array([np.array(i[1]) for i in dataset]) #label for the data