Inspect machine learning models
Project description
Model Inspector
Inspect machine learning models
Install
pip install model_inspector
How to Use
Example:
from IPython.display import HTML
import sklearn.datasets
from sklearn.linear_model import LinearRegression
from model_inspector.sklearn import generate_linear_model_html
diabetes = sklearn.datasets.load_diabetes()
X, y = diabetes["data"], diabetes["target"]
HTML(
generate_linear_model_html(
model=LinearRegression().fit(X, y),
feature_names=diabetes["feature_names"],
target_name="progression",
)
)
progression = 152.13
<span style='color:green'>- 10.01</span>
* <span style='color:blue'>age</span>
<span style='color:green'>- 239.82</span>
* <span style='color:blue'>sex</span>
<span style='color:green'>+ 519.84</span>
* <span style='color:blue'>bmi</span>
<span style='color:green'>+ 324.39</span>
* <span style='color:blue'>bp</span>
<span style='color:green'>- 792.18</span>
* <span style='color:blue'>s1</span>
<span style='color:green'>+ 476.75</span>
* <span style='color:blue'>s2</span>
<span style='color:green'>+ 101.04</span>
* <span style='color:blue'>s3</span>
<span style='color:green'>+ 177.06</span>
* <span style='color:blue'>s4</span>
<span style='color:green'>+ 751.28</span>
* <span style='color:blue'>s5</span>
<span style='color:green'>+ 67.63</span>
* <span style='color:blue'>s6</span>
HTML(
generate_linear_model_html(
LinearRegression().fit(X, y), diabetes["feature_names"], "progression"
)
)
progression = 152.13
<span style='color:green'>- 10.01</span>
* <span style='color:blue'>age</span>
<span style='color:green'>- 239.82</span>
* <span style='color:blue'>sex</span>
<span style='color:green'>+ 519.84</span>
* <span style='color:blue'>bmi</span>
<span style='color:green'>+ 324.39</span>
* <span style='color:blue'>bp</span>
<span style='color:green'>- 792.18</span>
* <span style='color:blue'>s1</span>
<span style='color:green'>+ 476.75</span>
* <span style='color:blue'>s2</span>
<span style='color:green'>+ 101.04</span>
* <span style='color:blue'>s3</span>
<span style='color:green'>+ 177.06</span>
* <span style='color:blue'>s4</span>
<span style='color:green'>+ 751.28</span>
* <span style='color:blue'>s5</span>
<span style='color:green'>+ 67.63</span>
* <span style='color:blue'>s6</span>
The library also supports logistic regression with model_inspector.sklearn.generate_logistic_model_html
.
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