.. _examples: Examples ======== `Transforming Features In The Iris Dataset `_ This is a version of part of the :mod:`sklearn` example `Feature importances with forests of trees `_. It illustrates retaining the semantic meaning of features as they are transformed. `Feature Importance In The Iris Dataset `_ This is a version of the :mod:`sklearn` example `Feature importances with forests of trees `_. It illustrates the consistent use of :mod:`pandas` data structures throughout the process. `Plotting Cross-Validated Predictions In The Boston Dataset `_ This is a version of the :mod:`sklearn` example `Plotting Cross-Validated Predictions `_. It further illustrates the consistent use of :mod:`pandas` data structures and :mod:`seaborn`, as well as using :mod:`ibex.xgboost`. `Confidence Intervals In The Digits Dataset `_ This is a version of the :mod:`sklearn` example `Pipelining: chaining a PCA and a logistic regression `_. It illustrates the use of pipelines. `Simple Row-Aggregating Features In The Movielens Dataset `_ This shows how to use :mod:`pandas`-munging estimators utilizing features which span multiple rows (instances). Pandas excels (no pun intended) in these kinds of operations. `Nonnegative Matrix Farcotization In The Movielens Dataset `_ This shows how to use :mod:`pandas`-munging estimators utilizing features which span multiple rows (instances), this time using `nonnegative matrix factorization `_. `Tensorflow/Keras Classification In The Iris Dataset `_ This example shows how to use :class:`ibex.tensorflow.contrib.keras.wrappers.scikit_learn.KerasClassifier`.