我正在處理一個涉及不得不使用以下形式的預處理數據的項目。「用序列設置數組元素」numpy error
數據說明上面已經給出過。目標是預測書面數字是否與所述數字的音頻相匹配。首先,我變換形式的所說陣列(N,13)的裝置在時間軸這樣:
這創建的(1,13),用於每一陣列的一致長度內發言。爲了在一個簡單的vanilla算法中測試它,我將這兩個數組壓縮在一起,以便我們創建一個形式數組(45000,2),當我將它插入到LogisticRegression類的fit函數中時,它會引發以下錯誤:
我在做什麼錯?
代碼:
import numpy as np
from sklearn.linear_model import LogisticRegression
match = np.load("/srv/digits/match_train.npy")
spoken = np.load("/srv/digits/spoken_train.npy")
written = np.load("/srv/digits/written_train.npy")
print(match.shape, spoken.shape, written.shape)
print(spoken[0].shape, spoken[1].shape)
def features(signal, function):
new = np.copy(signal)
for i in range(len(signal)):
new[i] = function(new[i], axis=0)
return new
spokenMean = features(spoken, np.mean)
print(spokenMean.shape, spokenMean[0])
result = np.array(list(zip(spokenMean,written)))
print(result.shape)
X_train, X_val, y_train, y_val = train_test_split(result, match, test_size =
0.33, random_state = 123)
model = LogisticRegression()
print(X_train.shape, y_train.shape)
model.fit(X_train, y_train)
yh_val = model.predict(X_val)
口語意思和ytrain的形狀是什麼? – Siddharth
@Siddharth口語意思不應該在適合功能,這當然應該是X_train。 X_train的形狀爲(30150,2); y_train的形狀爲(30150,)。 –
它仍然給X_train錯誤? – Siddharth