<jupyter_start><jupyter_text>Regression<jupyter_code>%matplotlib inline
%load_ext autoreload
%autoreload 2
import os
import sys
p = os.path.join(os.path.dirname('__file__'), '..')
sys.path.append(p)
from common import *<jupyter_output>The autoreload extension is already loaded. To reload it, use:
  %reload_ext autoreload<jupyter_text>Data  OLS * http://scikit-learn.org/stable/modules/linear_model.html<jupyter_code># Default is Ordinary Least Squares
# Minimizes sum-squared error between preds and targs
from sklearn.linear_model import LinearRegression<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.09880749574105621, 'fraction_numerical': 0.0017035775127768314, 'mean_word_length': 7.166666666666667, 'pattern_counts': {'":': 0, '<': 8, '<?xml version=': 0, '>': 8, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '413204', 'license': 'MIT', 'n_tokens_mistral': 212, 'n_tokens_neox': 203, 'n_words': 46, 'path': 'applied/Regression.ipynb', 'repo_name': 'jaingaurav3/ML_sample', 'size': '587'}