1
从https://github.com/llSourcell/predicting_stock_prices/blob/master/demo.py复制的代码 当我在jupyter笔记本中运行它挂起并挂在最后一行。我在笔记本电脑和下载文件夹中的.csv ......不知道这是错误Jupyter笔记本挂sklearn返回?
import csv
import numpy as np
from sklearn.svm import SVR
import matplotlib.pyplot as plt
#plt.switch_backend('newbackend')
dates = []
prices = []
def get_data(filename):
with open(filename, 'r') as csvfile:
csvFileReader = csv.reader(csvfile)
next(csvFileReader) # skipping column names
for row in csvFileReader:
dates.append(int(row[0].split('-')[0]))
prices.append(float(row[1]))
return
def predict_price(dates, prices, x):
dates = np.reshape(dates,(len(dates), 1)) # converting to matrix of n X 1
svr_lin = SVR(kernel= 'linear', C= 1e3)
svr_poly = SVR(kernel= 'poly', C= 1e3, degree= 2)
svr_rbf = SVR(kernel= 'rbf', C= 1e3, gamma= 0.1) # defining the support vector regression models
svr_rbf.fit(dates, prices) # fitting the data points in the models
svr_lin.fit(dates, prices)
svr_poly.fit(dates, prices)
plt.scatter(dates, prices, color= 'black', label= 'Data') # plotting the initial datapoints
plt.plot(dates, svr_rbf.predict(dates), color= 'red', label= 'RBF model') # plotting the line made by the RBF kernel
plt.plot(dates,svr_lin.predict(dates), color= 'green', label= 'Linear model') # plotting the line made by linear kernel
plt.plot(dates,svr_poly.predict(dates), color= 'blue', label= 'Polynomial model') # plotting the line made by polynomial kernel
plt.xlabel('Date')
plt.ylabel('Price')
plt.title('Support Vector Regression')
plt.legend()
plt.show()
return svr_rbf.predict(x)[0], svr_lin.predict(x)[0], svr_poly.predict(x)[0]
get_data('table.csv') # calling get_data method by passing the csv file to it
predicted_price = predict_price(dates, prices, 29)
我分了代码转换成细胞jupyter和
似乎挂起
predicted_priceIn [*]:
'plt.show()'会导致身材保持打开状态,并停止代码执行弗罗姆的其余部分。你可能想使用'plt.show(block = False)'。或者在脚本的最后一次调用'plt.show()'。 – DavidG
我不应该看到弹出的图吗? –
我尝试将
plt.show()
移动到最后,仍然遇到同一个摊位 –