Regression using Python

问题

I have the following variables:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split


np.random.seed(0)
n = 15
x = np.linspace(0,10,n) + np.random.randn(n)/5
y = np.sin(x)+x/6 + np.random.randn(n)/10


X_train, X_test, y_train, y_test = train_test_split(x, y, random_state=0)


def part1_scatter():
    %matplotlib notebook
    plt.figure()
    plt.scatter(X_train, y_train, label='training data')
    plt.scatter(X_test, y_test, label='test data')
    plt.legend(loc=4);

And the following question:

Write a function that fits a polynomial LinearRegression model on the training data X_train for degrees 1, 3, 6, and 9. (Use PolynomialFeatures in sklearn.preprocessing to create the polynomial features and then fit a linear regression model) For each model, find 100 predicted values over the interval x = 0 to 10 (e.g. np.linspace(0,10,100)) and store this in a numpy array. The first row of this array should correspond to the output from the model trained on degree 1, the second row degree 3, the third row degree 6, and the fourth row degree 9.

This is my code, but it don't work out:

def answer_one():
    from sklearn.linear_model import LinearRegression
    from sklearn.preprocessing import PolynomialFeatures

    np.random.seed(0)
n = 15
x = np.linspace(0,10,n) + np.random.randn(n)/5
y = np.sin(x)+x/6 + np.random.randn(n)/10

X_train, X_test, y_train, y_test = train_test_split(x, y, random_state=0)
results = []
pred_data = np.linspace(0,10,100)
degree = [1,3,6,9]
y_train1 = y_train.reshape(-1,1)

for i in degree:
    poly = PolynomialFeatures(degree=i)
    pred_poly1 = poly.fit_transform(pred_data[:,np.newaxis])
    X_F1_poly = poly.fit_transform(X_train[:,np.newaxis])
    linreg = LinearRegression().fit(X_F1_poly, y_train1)
    pred = linreg.predict(pred_poly1)
    results.append(pred)

    dataArray = np.array(results).reshape(4, 100)

    return dataArray

I receive this error:

    line 58      for i
in degree:      ^  IndentationError: unexpected
indent

Could you tell me where the problem is?

回答1:

The return statement should be performed after the for is done, so it should be indented under the for, not further in.

回答2:

At the start of your line

n = 15

You stopped with identing. So that part isn't recognized as the function. This can be solved by putting 4 spaces on all lines from n = 15 onwards.

来源：https://stackoverflow.com/questions/47845610/regression-using-python

标签

python

numpy

regression