Iris Classification on Keras

Iris Classification on Keras

Installation

Python3 版本为 3.6.4 : : Anaconda

conda install tensorflow==1.15.0
conda install keras==2.1.6

Code

# encoding:utf8

from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.metrics import classification_report
from keras.models import Sequential
from keras.layers import Dense, Activation
from keras.utils import to_categorical

if __name__ == '__main__':
    iris = load_iris()
    x_train, x_test, y_train, y_test = train_test_split(
        iris.data,
        iris.target,
        test_size=0.2,
        random_state=20)

    model = Sequential([
        Dense(8, input_dim=4),
        Activation('sigmoid'),
        Dense(8),
        Activation('relu'),
        Dense(3),
        Activation('softmax')
    ])
    model.compile(
        optimizer='Adam',
        loss='categorical_crossentropy',
        metrics=['accuracy']
    )
    model.fit(x_train, to_categorical(y_train, num_classes=3), epochs=70)
    y_pred = model.predict_classes(x_test)

    print(classification_report(y_test, y_pred, target_names=iris.target_names))

Errors

Traceback (most recent call last):
  File ".../Iris.py", line 32, in <module>
    y_pred = model.predict(x_train)
  File "...\Miniconda3\envs\tf\lib\site-packages\keras\engine\training.py", line 1169, in predict
    steps=steps)
  File "...\Miniconda3\envs\tf\lib\site-packages\keras\engine\training_arrays.py", line 300, in predict_loop
    outs.append(np.zeros(shape, dtype=batch_out.dtype))
TypeError: data type not understood

Solution: 重新配置环境，重新安装 keras, Tensorflow 等。

conda env list  # look up
conda remove -n [env name] --all  # delete