import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
data = pd.read_csv("ETHUSDT 15M.csv")
print(data.head())
print(data.corr())
sutun_isimler = ["Index","Zaman","Acılıs","Yuksek","Dusuk","Kapanıs","Hacim"]
data.columns = sutun_isimler
print(data.head())
data = data.drop(["Index"],axis=1)
data['Zaman'] = pd.to_numeric(pd.to_datetime(data['Zaman']))
a = data.iloc[152828:,:2]
b = data.iloc[152828:,-1]
x = pd.concat([a,b],axis=1)
y = data.drop(["Zaman","Acılıs","Hacim"],axis=1)
y = y.iloc[152828:,:]
X = x.values
Y = y.values
from sklearn.model_selection import train_test_split
x_train, x_test, y_train, y_test = train_test_split(X,Y,test_size=0.25,random_state=0)
from sklearn.linear_model import LinearRegression
lin_reg = LinearRegression()
lin_reg.fit(x_train,y_train)
lin_reg_predict = lin_reg.predict(x_test)
#num = pd.to_numeric(pd.to_datetime(["2022-12-27 06:00:00"]))
print(lin_reg.predict([[1672120800000000000,3800,1500]]))
#print(lin_reg.predict(pd.to_numeric(pd.to_datetime([“2022-12-27 06:00:00”]))[0],3800,1500))
from sklearn.preprocessing import PolynomialFeatures
x_poly = PolynomialFeatures(degree=3)
poly_reg = x_poly.fit_transform(x_train)
lin_reg_poly = LinearRegression()
lin_reg_poly.fit(poly_reg,y_train)
lin_reg_poly_predcit = lin_reg_poly.predict(x_poly.fit_transform(x_test))
print(lin_reg_poly.predict(x_poly.fit_transform([[1672120800000000000,3800,1500]])))
print(x_train.shape)
print(y_train.shape)
from sklearn.preprocessing import StandardScaler
sc1 = StandardScaler()
sc2 = StandardScaler()
x_trainsc = sc1.fit_transform(x_train)
y_trainsc = sc2.fit_transform(y_train)
from sklearn.svm import SVR
svr = SVR(kernel="rbf")
svr.fit(x_trainsc,y_trainsc)
svr_predict = svr.predict(x_test)
#print(svr.predict([[1672120800000000000,3800,1500]]))
from sklearn.svm import SVR
svr = SVR(kernel=“rbf”)
svr.fit(x_trainsc,y_trainsc)
svr_predict = svr.predict(x_test)
#print(svr.predict([[1672120800000000000,3800,1500]]))
ekledigim zaman
ValueError: y should be a 1d array, got an array of shape (25255, 3) instead.
bu tarzda hata alıyorumn sebebi nedir ?