[docs] gitbook migrated (#1059)

* updated the format

* updated the summary

* fixed the format

* added the format

* fixed the format in gs

* fixed the tabs format

---------

Co-authored-by: Rakavitha Kodhandapani <seldon@SELIN002.local>

Author: Rajakavitha1

docs-gb/SUMMARY.md

@@ -1,94 +1,99 @@
 # Table of contents
 
-* [README](README.md)
-
 ## Overview
 
-* [Introduction](source/overview/README.md)
+* [Introduction](source/overview/high_level.md)
 * [Getting Started](source/overview/getting_started.md)
 * [Algorithm Overview](source/overview/algorithms.md)
 * [White-box and black-box models](source/overview/white_box_black_box.md)
 * [Saving and loading](source/overview/saving.md)
 * [Frequently Asked Questions](source/overview/faq.md)
 
 ## Explanations
-
-* [Explanations](source/explanations/README.md)
-  * [Examples](source/explanations/examples.md)
-  * [Methods](source/explanations/methods.md)
-  * [methods](source/methods/README.md)
-    * [ALE](source/methods/ale.md)
-    * [Anchors](source/methods/anchors.md)
-    * [CEM](source/methods/cem.md)
-    * [CF](source/methods/cf.md)
-    * [CFProto](source/methods/cfproto.md)
-    * [CFRL](source/methods/cfrl.md)
-    * [IntegratedGradients](source/methods/integratedgradients.md)
-    * [KernelSHAP](source/methods/kernelshap.md)
-    * [LinearityMeasure](source/methods/linearitymeasure.md)
-    * [PartialDependence](source/methods/partialdependence.md)
-    * [PartialDependenceVariance](source/methods/partialdependencevariance.md)
-    * [PermutationImportance](source/methods/permutationimportance.md)
-    * [ProtoSelect](source/methods/protoselect.md)
-    * [Similarity](source/methods/similarity.md)
-    * [TreeSHAP](source/methods/treeshap.md)
-    * [TrustScores](source/methods/trustscores.md)
-    * [ALE Figures](source/methods/ale_figures.md)
-
-## Model Confidence
-
-* [confidence](source/confidence/README.md)
-  * [Examples](source/confidence/examples.md)
-  * [Methods](source/confidence/methods.md)
-  * [examples](source/examples/README.md)
+* Methods
+  * [ALE](source/methods/ale.md)
+  * [Anchors](source/methods/anchors.md)
+  * [CEM](source/methods/cem.md)
+  * [CF](source/methods/cf.md)
+  * [CFProto](source/methods/cfproto.md)
+  * [CFRL](source/methods/cfrl.md)
+  * [IntegratedGradients](source/methods/integratedgradients.md)
+  * [KernelSHAP](source/methods/kernelshap.md)
+  * [LinearityMeasure](source/methods/linearitymeasure.md)
+  * [PartialDependence](source/methods/partialdependence.md)
+  * [PartialDependenceVariance](source/methods/partialdependencevariance.md)
+  * [PermutationImportance](source/methods/permutationimportance.md)
+  * [ProtoSelect](source/methods/protoselect.md)
+  * [Similarity](source/methods/similarity.md)
+  * [TreeSHAP](source/methods/treeshap.md)
+  * [TrustScores](source/methods/trustscores.md)
+* Examples
+  * [Alibi Overview Examples](source/examples/overview.md)
+  * Accumulated Local Effets
     * [Accumulated Local Effects for classifying flowers](source/examples/ale_classification.md)
     * [Accumulated Local Effects for predicting house prices](source/examples/ale_regression_california.md)
+  * Anchors
     * [Anchor explanations for fashion MNIST](source/examples/anchor_image_fashion_mnist.md)
     * [Anchor explanations for ImageNet](source/examples/anchor_image_imagenet.md)
     * [Anchor explanations for income prediction](source/examples/anchor_tabular_adult.md)
     * [Anchor explanations on the Iris dataset](source/examples/anchor_tabular_iris.md)
     * [Anchor explanations for movie sentiment](source/examples/anchor_text_movie.md)
+  * Contrastive Explanation Method
     * [Contrastive Explanations Method (CEM) applied to Iris dataset](source/examples/cem_iris.md)
     * [Contrastive Explanations Method (CEM) applied to MNIST](source/examples/cem_mnist.md)
-    * [Counterfactual instances on MNIST](source/examples/cf_mnist.md)
+  * [Counterfactual Instances on MNIST](source/examples/cf_mnist.md)
+  * Counterfactuals Guided by Prototypes
     * [Counterfactual explanations with one-hot encoded categorical variables](source/examples/cfproto_cat_adult_ohe.md)
     * [Counterfactual explanations with ordinally encoded categorical variables](source/examples/cfproto_cat_adult_ord.md)
     * [Counterfactuals guided by prototypes on California housing dataset](source/examples/cfproto_housing.md)
     * [Counterfactuals guided by prototypes on MNIST](source/examples/cfproto_mnist.md)
+  * Counterfactuals with Reinforcement Learning
     * [Counterfactual with Reinforcement Learning (CFRL) on Adult Census](source/examples/cfrl_adult.md)
     * [Counterfactual with Reinforcement Learning (CFRL) on MNIST](source/examples/cfrl_mnist.md)
-    * [Distributed KernelSHAP](source/examples/distributed_kernel_shap_adult_lr.md)
+  * Integrated Gradients
     * [Integrated gradients for a ResNet model trained on Imagenet dataset](source/examples/integrated_gradients_imagenet.md)
     * [Integrated gradients for text classification on the IMDB dataset](source/examples/integrated_gradients_imdb.md)
     * [Integrated gradients for MNIST](source/examples/integrated_gradients_mnist.md)
     * [Integrated gradients for transformers models](source/examples/integrated_gradients_transformers.md)
-    * [Explaining Tree Models with Interventional Feature Perturbation Tree SHAP](source/examples/interventional_tree_shap_adult_xgb.md)
+  * Kernel SHAP
+    * [Distributed KernelSHAP](source/examples/distributed_kernel_shap_adult_lr.md)
     * [KernelSHAP: combining preprocessor and predictor](source/examples/kernel_shap_adult_categorical_preproc.md)
     * [Handling categorical variables with KernelSHAP](source/examples/kernel_shap_adult_lr.md)
     * [Kernel SHAP explanation for SVM models](source/examples/kernel_shap_wine_intro.md)
     * [Kernel SHAP explanation for multinomial logistic regression models](source/examples/kernel_shap_wine_lr.md)
-    * [Linearity measure applied to fashion MNIST](source/examples/linearity_measure_fashion_mnist.md)
-    * [Linearity measure applied to Iris](source/examples/linearity_measure_iris.md)
-    * [Alibi Overview Example](source/examples/overview.md)
-    * [Explaining Tree Models with Path-Dependent Feature Perturbation Tree SHAP](source/examples/path_dependent_tree_shap_adult_xgb.md)
-    * [Feature importance and feature interaction based on partial dependece variance](source/examples/pd_variance_regression_friedman.md)
+  * Partial Dependence
     * [Partial Dependence and Individual Conditional Expectation for predicting bike renting](source/examples/pdp_regression_bike.md)
-    * [Permutation Feature Importance on "Who's Going to Leave Next?"](source/examples/permutation_importance_classification_leave.md)
-    * [ProtoSelect on Adult Census and CIFAR10](source/examples/protoselect_adult_cifar10.md)
+  * Partial Dependence Variance
+    * [Feature importance and feature interaction based on partial dependece variance](source/examples/pd_variance_regression_friedman.md)
+  * Permutation Importance
+    * [Permutation Feature Importance on “Who’s Going to Leave Next?”](source/examples/permutation_importance_classification_leave.md)
+  * Similarity explanations
     * [Similarity explanations for 20 newsgroups dataset](source/examples/similarity_explanations_20ng.md)
     * [Similarity explanations for ImageNet](source/examples/similarity_explanations_imagenet.md)
     * [Similarity explanations for MNIST](source/examples/similarity_explanations_mnist.md)
+  * Tree SHAP
+    * [Explaining Tree Models with Interventional Feature Perturbation Tree SHAP](source/examples/interventional_tree_shap_adult_xgb.md)
+    * [Explaining Tree Models with Path-Dependent Feature Perturbation Tree SHAP](source/examples/path_dependent_tree_shap_adult_xgb.md)
+
+## Model Confidence
+
+* Methods
+  * [Measuring the linearity of machine learning models](source/methods/linearitymeasure.md)
+  * [Trust Scores](source/methods/trustscores.md)
+* Examples
+  * Measuring the linearity of machine learning models
+    * [Linearity measure applied to fashion MNIST](source/examples/linearity_measure_fashion_mnist.md)
+    * [Linearity measure applied to Iris](source/examples/linearity_measure_iris.md)
+  * Trust Scores
     * [Trust Scores applied to Iris](source/examples/trustscore_iris.md)
     * [Trust Scores applied to MNIST](source/examples/trustscore_mnist.md)
-    * [A Gradient Boosted Tree Model for the Adult Dataset](source/examples/xgboost_model_fitting_adult.md)
-  * [Methods](model-confidence/confidence/methods-1.md)
-  * [Examples](model-confidence/confidence/examples-2.md)
 
 ## Prototypes
-
-* [prototypes](source/prototypes/README.md)
-  * [Examples](source/prototypes/examples.md)
-  * [Methods](source/prototypes/methods.md)
+  * Methods
+    * [ProtoSelect](source/methods/protoselect.md)
+  * Examples
+    * [ProtoSelect on Adult Census and CIFAR10](source/examples/protoselect_adult_cifar10.md)
+  
 
 ## API Reference