Question

我正在尝试使用PyBrain进行预测，但我的代码输出在测试集上给出了几乎总是相同的预测。谁能解释我为什么？

谢谢！

## ----------------------- Data ---------------------------- ##
import pandas as pd

bdata = pd.read_csv(r'C:\Users\philippe.colo\Projects\regret\data\MT_161.csv', delimiter=';', na_values=0, nrows=96*3,
                     index_col=0, parse_dates=True, infer_datetime_format=True)

# 0: weekday, 1: month, 2: time, 3: monthday

X = []

for k, v in bdata.iterrows():
    dow = k.dayofweek
    day = k.day
    mth = k.month
    sec = k.hour * 3600 + k.minute * 60
    X.append([dow, day, mth, sec])

Y = bdata.values

from pybrain.datasets import SupervisedDataSet
DS = SupervisedDataSet(4, 1)
for i in range(0, 96*2):
        DS.addSample((X[i][0], X[i][1], X[i][2], X[i][3],), (float(Y[i]),))


## ----------------------- ANN ---------------------------- ##

from pybrain.structure import FeedForwardNetwork
n = FeedForwardNetwork()

from pybrain.structure import LinearLayer, SigmoidLayer
from pybrain.structure import FullConnection

n.addInputModule(LinearLayer(4, name='in'))
n.addModule(SigmoidLayer(3, name='hidden'))
n.addOutputModule(LinearLayer(1, name='out'))
n.addConnection(FullConnection(n['in'], n['hidden'], name='c1'))
n.addConnection(FullConnection(n['hidden'], n['out'], name='c2'))

n.sortModules() #initialisation


## ----------------------- Trainer ---------------------------- ##

from pybrain.supervised.trainers import BackpropTrainer

tstdata, trndata = DS.splitWithProportion(0.25)

#print len(tstdata)
#print len(trndata)

trainer = BackpropTrainer(module=n, dataset=DS)

#print trainer.trainUntilConvergence()
trainer.trainOnDataset(trndata, 100)


print n.activate((2, 1, 3, 0))
print n.activate((2, 1, 3, 90))

我的代码的第一部分只是数据集。然后是人工神经网络，最后是训练师。我怀疑训练师的编码完全错误。

为什么Pybrain总是预测相同的值？

0 个答案: