<jupyter_start><jupyter_text>Step 4: Scikit-learn 4-Step Modeling Pattern (Digits Dataset) Import the [model](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) you want to useIn sklearn, all machine learning models are implemented as Python classes<jupyter_code>from sklearn.linear_model import LogisticRegression<jupyter_output><empty_output><jupyter_text>Make an instance of the [Model](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html)<jupyter_code># all parameters not specified are set to their defaults
### ADJUST THE CODE SO THE WARNINGS DON'T APPEAR
logisticRegr = LogisticRegression()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.09090909090909091, 'fraction_numerical': 0.002797202797202797, 'mean_word_length': 8.063291139240507, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, 'https://': 2, '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': '130478', 'license': 'MIT', 'n_tokens_mistral': 228, 'n_tokens_neox': 219, 'n_words': 52, 'path': 'Solutions_4_Logistic_Regression_using_Python.ipynb', 'repo_name': 'atlas-github/20190731SMG', 'size': '715'}