Index
A
- A/B testing, Testing Production Systems
- accuracy, Evaluating the Model, Relation to accuracy
- acknowledgments, From Andreas
- adjusted rand index (ARI), Evaluating clustering with ground truth
- agglomerative clustering
- evaluating and comparing, Evaluating clustering with ground truth
- example of, Agglomerative Clustering
- hierarchical clustering, Hierarchical clustering and dendrograms
- linkage choices, Agglomerative Clustering
- principle of, Agglomerative Clustering
- algorithm chains and pipelines, Algorithm Chains and Pipelines-Summary and Outlook
- building pipelines, Building Pipelines
- building pipelines with make_pipeline, Convenient Pipeline Creation with make_pipeline-Accessing Attributes in a Pipeline inside GridSearchCV
- grid search preprocessing steps, Grid-Searching Preprocessing Steps and Model Parameters
- grid-searching for model selection, Grid-Searching Which Model To Use
- importance of, Algorithm Chains and Pipelines
- overview of, Summary and Outlook
- parameter selection with preprocessing, Parameter Selection with Preprocessing
- pipeline interface, The General Pipeline Interface
- using pipelines in grid searches, Using Pipelines in Grid Searches-Using Pipelines in Grid Searches
- algorithm parameter, Estimating complexity in neural networks
- algorithms (see also models; problem solving)
- evaluating, Generalization, Overfitting, and Underfitting
- minimal code to apply to algorithm, Summary and Outlook
- sample datasets, Some Sample Datasets-Some Sample Datasets
- scaling
- MinMaxScaler, Preprocessing data for ...
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