scaler.py

def create_dataset(signal_data, look_back=1):
    dataX, dataY = [], []
    for i in range(len(signal_data) - look_back):
        dataX.append(signal_data[i:(i + look_back), :])
        dataY.append(signal_data[i + look_back, -1])
    return np.array(dataX), np.array(dataY)



look_back = 20

stock = 'kospi.csv'
df = pd.read_csv(stock)

signal_data = df[["close", "volume"]].values.astype('float32')


scaler = MinMaxScaler()
signal_data = scaler.fit_transform(signal_data)

train_size = int(len(signal_data) * 0.80)
test_size = len(signal_data) - train_size
train = signal_data[0:train_size]
test = signal_data[train_size:]


# train, test = stock_price[0:train_size,:], stock_price[train_size:len(stock_price),:]

# 데이터셋 생성
x_train, y_train = create_dataset(train, look_back)
x_test, y_test = create_dataset(test, look_back)

after create_dataset

scx = StandardScaler()
scy = StandardScaler()

x_train = scx.fit_transform(x_train)
x_test = scx.fit_transform(x_test)
y_train = scy.fit_transform(y_train)

Then ValueError: Found array with dim 3. StandardScaler expected <= 2. occur