evalml
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alteryx
EvalML is an AutoML library written in python.
[Diabetes Predicttion Using EvalML.txt](https://github.com/alteryx/evalml/files/10026684/Diabetes.Predicttion.Using.EvalML.txt) X_train, X_test, y_train, y_test = evalml.preprocessing.split_data(x, y, problem_type='binary') >>>>>>> Which runs fine from evalml.automl import AutoMLSearch automl = AutoMLSearch(X_train=X_train, y_train=y_train, problem_type='binary') >>>>>>>>>>> Also run fine automl.search()...
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- The current [Start guide](https://evalml.alteryx.com/en/stable/start.html) is too long for a first time user. There is too much text and information being presented to a first time user - We need...
- As a user, I wish I could use the Ordinal Encoder to encode Ordinal columns whose categories' orders are not in strictly increasing numeric order. The following code raises...
Hello, I have been using EvalML for a while and now I tried running analyses on more complex data, while setting a small `time_budget` value to observe how it behaves....
After fast mode is added, we should add it to EvalML docs so we can tell users about fast mode, its benefits, and its limitations.
Partial dependence fast mode was initially added with some limitations, namely that it will not produce correct results if any of the components in the pipeline relies on multiple columns...
In partial dependence fast mode, we precompute `pipeline.transform_all_but_final(X_eval)`, which allows us to determine if a feature will have an impact on model results and, if it won't, use averaged predictions...
In the initial implementation of partial dependence fast mode in #3753, the Oversampler was causing a few pipelines to produce different partial dependence results in fast mode. After understanding why...
we might want to move [unsupported decomposer frequencies] either 1.) into the stl_decomposer module and/or 2.) make it returnable by the decomposer itself. Then we can dynamically know what decomposers...
