Predicted PE in neatly ALEXANDER D displays the traditional vary and variation. Prediction accuracy is 77%.

1–2–2 Feature Extraction

Having a restricted set of options on this dataset can lead us to consider extracting some knowledge from the present dataset. First, we will convert the formation express knowledge into numeric knowledge. Our background wisdom can assist us to bet that some facies are perhaps provide extra in a selected formation reasonably than others. We can use the LabelEncoder serve as:

We transformed formation class knowledge into numeric to make use of as a predictor and added 1 to start out predictor from 1 as an alternative of 0. To see if new characteristic extraction would lend a hand prediction development, we must outline a baseline style then examine it with the extracted characteristic style.

Baseline Model Performance

For simplicity, we will be able to use a logistic regression classifier as a baseline style and can read about style efficiency with a cross-validation idea. Data shall be cut up into 10 subgroups and the method shall be repeated three times.

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