陀螺仪4.4.3
我用import numpy
import matplotlib.pyplot as plt
import pandas
from keras.models import Sequential
from keras.layers import Dense
import math
# convert an array of values into a dataset matrix
def create_dataset(dataset, look_back=1):
dataX, dataY = [], []
for i in range(len(dataset)-look_back-1):
a = dataset[i:(i+look_back), 0]
dataX.append(a)
dataY.append(dataset[i + look_back, 0])
return numpy.array(dataX), numpy.array(dataY)
# load the dataset
dataframe = pandas.read_csv('Data.csv', usecols=[1], engine='python')
dataset = dataframe.values
dataset = dataset.astype('float32')
# split into train and test sets
train_size = int(len(dataset) * 0.67)
test_size = len(dataset) - train_size
train, test = dataset[0:train_size,:], dataset[train_size:len(dataset),:]
# reshape dataset
look_back = 6
trainX, trainY = create_dataset(train, look_back)
testX, testY = create_dataset(test, look_back)
# create and fit Multilayer Perceptron model
model = Sequential();
model.add(Dense(20, input_dim=look_back, activation='relu'))
model.add(Dense(16, activation='relu'))
model.add(Dense(1))
model.compile(loss='mean_squared_error', optimizer='adam')
model.fit(trainX, trainY, epochs=400, batch_size=2, verbose=2)
# Estimate model performance
trainScore = model.evaluate(trainX, trainY, verbose=0)
print('Train Score: %.2f MSE (%.2f RMSE)' % (trainScore, math.sqrt(trainScore)))
testScore = model.evaluate(testX, testY, verbose=0)
print('Test Score: %.2f MSE (%.2f RMSE)' % (testScore, math.sqrt(testScore)))
# generate predictions for training
trainPredict = model.predict(trainX)
testPredict = model.predict(testX)
设置了Header Filter。
输入过滤器输入，过滤数据，但不过滤选择组合。
我可以滚动并从组合菜单中选择一个选项，也可以对其进行过滤。
有解决方法吗？
不确定该怎么办。
Select Option我希望键入的值与选择组合相匹配。