我尝试使用这段代码预测10个类
#Predicting the Test set rules
y_pred = model.predict(traindata)
y_pred = np.argmax(y_pred, axis=1)
y_true = np.argmax(testdata, axis=1)
target_names = ["akLembut","akMundur","akTajam","caMenaik", "caMenurun", "coretanTengah", "garisAtas", "garisBawah", "garisBawahBanyak", "ttdCangkang"]
print("\n"+ classification_report(y_true, y_pred, target_names=target_names))
但后来我收到了这样的错误信息
AxisError Traceback (most recent call last)
<ipython-input-13-a2b02b251547> in <module>()
2 y_pred = model.predict(traindata)
3 y_pred = np.argmax(y_pred, axis=1)
----> 4 y_true = np.argmax(testdata, axis=1)
5
6 target_names = ["akLembut","akMundur","akTajam","caMenaik", "caMenurun", "coretanTengah", "garisAtas", "garisBawah", "garisBawahBanyak", "ttdCangkang"]
<__array_function__ internals> in argmax(*args, **kwargs)
2 frames
/usr/local/lib/python3.6/dist-packages/numpy/core/fromnumeric.py in _wrapit(obj, method, *args, **kwds)
45 except AttributeError:
46 wrap = None
---> 47 result = getattr(asarray(obj), method)(*args, **kwds)
48 if wrap:
49 if not isinstance(result, mu.ndarray):
AxisError: axis 1 is out of bounds for array of dimension 1
我已经对数据进行了训练,我需要知道每个数据的准确性
我猜你的
test_data
数组只是一维的,所以改为y_true = np.argmax(testdata, axis=0)
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