If needed, register your original prediction model by following the steps in Deploy models with Azure Machine Learning. Create a scoring file. Python Copy %%writefile score.py import json import numpy as np import pandas as pd import os import pickle from sklearn.externals import joblib from ...
numpy>=1.15.2 pandas>=0.19.2 matplotlib>=3.1.3 scikit-learn>=0.23.0 pip install gaminet To use it on GPU, conda install tensorflow==2.2, pip install tensorflow-lattice==2.0.8, conda install tensorflow-estimators==2.2 Usage Import library ...
SHAP has specific support for natural language models like those in the Hugging Face transformers library. By adding coalitional rules to traditional Shapley values we can form games that explain large modern NLP model using very few function evaluations. Using this functionality is as simple as pass...
numpy arrays, torch tensors, pandas DataFrames, Python dictionaries holding heterogeneous data, external/custom datasets like ImageFolder from torchvision. We’ve put extra effort to make these work well with sklearn. If this is not enough to satisfy your customization needs, we...
If needed, register your original prediction model by following the steps inDeploy models with Azure Machine Learning. Create a scoring file. PythonCopy %%writefile score.pyimportjsonimportnumpyasnpimportpandasaspdimportosimportpicklefromsklearn.externalsimportjoblibfromsklearn.linear_modelimportLogisticRegre...
frominterpret.glassboximportExplainableBoostingClassifierebm=ExplainableBoostingClassifier()ebm.fit(X_train,y_train)# or substitute with LogisticRegression, DecisionTreeClassifier, RuleListClassifier, ...# EBM supports pandas dataframes, numpy arrays, and handles "string" data natively. ...
"SALib: An open-source Python library for Sensitivity Analysis" (J. D. Herman and W. Usher 2017) @article{herman2017salib, title={SALib: An open-source Python library for Sensitivity Analysis.}, author={Herman, Jonathan D and Usher, Will}, journal={J. Open Source Software}, volume={2...
In the example below we have explained how the 7th intermediate layer of the VGG16 ImageNet model impacts the output probabilities. from keras.applications.vgg16 import VGG16 from keras.applications.vgg16 import preprocess_input import keras.backend as K import numpy as np import json import ...
SHAP has specific support for natural language models like those in the Hugging Face transformers library. By adding coalitional rules to traditional Shapley values we can form games that explain large modern NLP model using very few function evaluations. Using this functionality is as simple as pass...
SHAP has specific support for natural language models like those in the Hugging Face transformers library. By adding coalitional rules to traditional Shapley values we can form games that explain large modern NLP model using very few function evaluations. Using this functionality is as simple as pass...