I learned to learn machine learning, and I came across a youtube siraj and his Udacity video and wanted to try and pick up a few things.
His video is in the link: https://www.youtube.com/watch?v=vOppzHpvTiQ&index=1&list=PL2-dafEMk2A7YdKv4XfKpfbTH5z6rEEj3
In his video, he had a txt file that he imported and read, but when I tried to recreate the txt file, it could not be read correctly. Instead, I tried to create a pandas framework with the same data and perform linear regression / prediction on it, but then I got the following error.
Found input variables with inconsistent number of samples: [1, 16] and something about passing 1d arrays, and I need to change them.
Then, when I tried to change them after this post: Sklearn: ValueError: found input variables with inconsistent number of samples: [1, 6]
I get this error ....
figures (1,16) and (1,1) are not aligned: 16 (dim 1)! = 1 (dim 0)
This is my code below. I know this is probably a syntax error, I am not familiar with this scklearn yet and I need help.
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from sklearn import linear_model
DF = pd.DataFrame()
DF['Brain'] = [3.385, .480, 1.350, 465.00,36.330, 27.660, 14.830, 1.040, 4.190, 0.425, 0.101, 0.920, 1.000, 0.005, 0.060, 3.500 ]
DF['Body'] = [44.500, 15.5, 8.1, 423, 119.5, 115, 98.2, 5.5,58, 6.40, 4, 5.7,6.6, .140,1, 10.8]
try:
x = DF['Brain']
y = DF['Body']
x = x.tolist()
y = y.tolist()
x = np.asarray(x)
y = np.asarray(y)
body_reg = linear_model.LinearRegression()
body_reg.fit(x.reshape(-1,1),y.reshape(-1,1))
plt.scatter(x,y)
plt.plot(x,body_reg.predict(x))
plt.show()
except Exception as e:
print(e)
Can anyone explain why sklearn doesn't like my input?