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Outline for new docs

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1 parent 5fc80fc commit 8618ce673e49b95f40c9659319c3cb72281dacac Ken Van Haren committed Nov 11, 2015
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  1. +20 −10 docs/source/index.rst
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@@ -11,22 +11,32 @@ existing python machine learning and statistics libraries (scikit-learn, rpy2, e
Features
^^^^^^^^
-* Fast caching and persistence of all intermediate and final calculations -- nothing is recomputed unnecessarily.
-* Advanced training and preparation logic. Ramp respects the current training set, even when using complex trained features and blended predictions, and also tracks the given preparation set (the x values used in feature preparation -- e.g. the mean and stdev used for feature normalization.)
-* A growing library of feature transformations, metrics and estimators. Ramp's simple API allows for easy extension.
+* Easy and methodical model comparison and evaluation
+* Clean components for features, models, and results
+* Comprehensive suite of tools for measuring, validating, and building, blending, and composing models.
+* Easily extensible API
Contents:
.. toctree::
:maxdepth: 2
- intro
- Data contexts <context>
- configurations
- features
- stores
- estimators
- reporters
+ Overview
+ Tasks
+ Classification
+ Regression
+ Timeseries
+ Clustering
+ Sequence labeling
+ Model comparison and evaluation
+ Cross-validation (fold generation)
+ Metrics, reports, and plots
+ Features
+ Model blending and composition
+ Productionizing
+ [Feature selection]
+ API
+
Indices and tables

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