신경망(2)
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[신경망] RNN을 이용한 주식가격 예측 알고리즘 코드
데이터 코드 import tensorflow as tf import numpy as np import matplotlib.pyplot as plt import pandas as pd import seaborn as sns def MinMaxScaler(data): denom=np.max(data,0)-np.min(data,0) nume=data-np.min(data,0) return nume/denom #정규화 path = "C:\\Users\\student\\Desktop\\DY\\★ 데이터\\105. deep-learning-dataset\\" xy=np.loadtxt(path+"data-02-stock_daily.csv", delimiter=",", skiprows=0+1+1) xy=xy[::-1]..
2020.05.07 -
[신경망] 선형회귀로 분류가 불가능한 경우(XOR problem)
xdata = np.array([[0,0],[0,1],[1,0],[1,1]]) ydata = np.array([[0],[1],[1],[0]]) 텐서플로우 기반 단일 퍼셉트론 x = tf.placeholder(tf.float32, [None,2]) y = tf.placeholder(tf.float32, [None,1]) # 0~9 digit w = tf.Variable(tf.random_normal([2,1])) b = tf.Variable(tf.random_normal([1])) hf= tf.sigmoid(tf.matmul(x, w) + b) cost = -tf.reduce_mean(y * tf.log(hf) + (1 - y) * tf.log(1 - hf)) train = tf.train.Gradient..
2020.04.21