[tensorflow] 1D CNN

1D CNN의 간략한 예제코드를 공유한다.

python과 R을 동시에 포스팅 하는 것이 좋아보여, 앞으로는 같이 포스팅하고자 한다.

https://rcj92.tistory.com/14

1D-CNN & Multi input Multi output Model in R

 

import pandas as pd
import numpy as np
import tensorflow as tf
import keras
import statsmodels.api as sm
# https://ehfgk78.github.io/2018/01/21/DataScience07TimeSeriesData01/
df = sm.datasets.get_rdataset("AirPassengers").data
df=df.set_index('time')
as_ts=df[df.index<1956]
as_ts_test=df[df.index>=1956]
data=as_ts_test
def data_generate(data):
  tr=np.array(data).flatten()
  tr_xs=list();tr_ys=list()
  for i in range((len(tr)-36)):
    tr_xs.append(tr[i:(i+23+1)][np.newaxis,:])
    tr_ys.append(tr[(i+13):(i+36+1)][np.newaxis,:])

  tr_x=np.concatenate(tr_xs,axis=0)[:,:,np.newaxis]
  tr_y=np.concatenate(tr_ys,axis=0)[:,:,np.newaxis]
  return tr_x,tr_y
  

tr_x,tr_y=data_generate(as_ts)
te_x,te_y=data_generate(as_ts_test)

model=keras.Sequential()
model.add(keras.layers.Conv1D(filters=64,kernel_size=3,input_shape=(24,1),padding='valid',activation='relu'))
model.add(keras.layers.MaxPooling1D(pool_size=4))
model.add(keras.layers.Flatten())
model.add(keras.layers.Dense(units=24))

model.compile(
  loss='mae',
  optimizer='adam',
  metrics=['mae']
)
model.summary()
model.fit(x=tr_x,y=tr_y[:,:,0],batch_size=3,epochs=600)