Index
A
Artificial intelligence (AI)
B
Backpropagation neural networks
Bagging
Boosting
C
Captum
Catboost model
Causal factors
Classical predictive modeling
Classification model
Convolutional neural network layer
D
Decision tree classification model
Decision tree model
Deep learning (DL)
kernel-based explainer, Keras
MNIST
PyTorch
sequential information processing
Deep neural network models
Descent-based boosting model
E, F
ELI5 library
ELI5 permutation library
Ensemble models
bagging
catboost model
catboost model interpretation
classification model
EBM
EBM classifier
ELI5 explainer
ELI5 permutation library
extreme gradient boosting–based regressor
global feature importance
global/local explainable libraries
LIME explainer
mixed input feature data, SHAP
multiclass classification problems
nonlinear classifier, class probabilities
partial dependency plot
random forest classifier
random forest model
random forest regressor
RF
XGBoost model
XGBoost regressor
Explainability libraries
LIME installation
methods
SHAPASH
SHAP installation
Skater installtion
Skope-rule
Explainable boosting machine (EBM)
Explained nonlinear decision tree–based models
explainer function
Extreme gradient boosting model
G, H, I, J
Generalized additive model (GAM)
K
Keras-based deep learning model
L
LIME library
Linear classifier
Linear models
Linear regression model
Logistic regression model
M
Machine learning (ML)
Modern predictive modeling
Multiple hidden layer neural networks
N, O
Natural language processing
local explanation, ELI5
problems
sentiment analysis prediction
ELI5
SHAP
text classification
Nonlinear classifier
Nonlinear model
benefits
class probabilities
decision tree classifier
definition
ELI5 library
ELI5 permutation library
LIME explainer
local explanations, LIME
mixed input features
model explanations, ELI5
partial dependency plot, tree explainer
SHAP partial dependency plot
SHAP values
tree-based regression model
Nonlinear models
P, Q
Permutation approach
pip command
Python-based libraries
PyTorch
R
Random forest (RF)
Recurrent neural networks
S
Scikit-learn library
SHAPASH library
Shapely additive explanations (SHAP)
Single hidden layer neural network model
Skater
SP-LIME module
Stacking
Supervised learning model
classifier
class probabilities
definition
ELI5
LIME
local explainable libraries
logistic regression model
multinomial output variables
regression model
AI numerical input variables
mixed features
mixed input feature
mixed input variables
numerical features
partial dependency, mixed input
scaled data
SHAP partial dependency plot
regression model, numerical features
T
TF-IDF vectorizer
Time-series modeling
components
definition
LIME
SHAP
Tree-based nonlinear model
Tree-based regression model
U, V, W
UCI machine learning repository
UCI ML repository
X, Y, Z
XGBoost model
XGB regressor
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