Questions tagged [pipelines]

A pipeline is a sequence of functions (or the equivalent thereof), composed so that the output of one is input for the next, in order to create a compound transformation. Famously, a shell pipeline looks like "command | command2 | command3" (but use the tag "pipe" for this). It's also used in computer architecture to define a sequence of serial stages that execute in parallel over elements being fed into a pipe, in order to increase the overall throughput.

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Segment Data in SKlearn Pipeline

I have one dataset, and I would like to split this dataset into two segments - representing two different groups of people. I have created two separate binary classifiers for these two groups. What ...
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Error encoding categorical features using sklearn pipelines

I am new to sklearn pipelines and am using this post as a guide for my code: https://www.codementor.io/bruce3557/beautiful-machine-learning-pipeline-with-scikit-learn-uiqapbxuj I am trying to encode ...
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R has {drake} which makes it easy to make reproducible data pipelines. Does Python have a similar package?

See R's {drake}. It allows you to define a reproducible pipeline ...
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195 views

How to use Tensorflow Model Zoo frozen graphs in an Estimator pipeline?

As Tensorflow* says on their website, the Estimators API should genereally make most ML tasks more friendly. In the past I've been using Tensorflow's Model Zoo for object detection as I didn't (and ...
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116 views

how to pass parameters over sklearn pipeline's stages?

I'm working on a deep neural model for text classification using Keras. To fine tune some hyperparameters i'm using Keras Wrappers for the Scikit-Learn API. So I builded a Sklearn Pipeline for that: <...
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109 views

Using a LinearSVC() for multilabel classification with MultiOutputClassifier() in a pipeline in sci-kit learn

My input data is a (23948,) pandas.Series of strings containing newspaper headlines. My target are 20 labels of the headline (e.g. 'crime', 'politics') each binarily encoded with [0, 1]. The labels ...
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Scalable Data Science Pipeline

I was looking at this repository (https://github.com/jeffheaton/jh-kaggle-util) and was wondering if there's a better approach to creating a scalable machine learning pipeline for data science ...
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110 views

Difference between sklearn make_pipeline and imblearn make_pipeline

Can anybody please explain the difference between sklearn.pipeline.make_pipline and imblearn.pipeline.make_pipline.
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How to deal with evaluations in a multi step ML pipeline

Apache Spark provides us the pipeline to construct a ML pipeline. Moreover, we can evaluate the regressors in the pipeline, now here is the point I dont understand: how to apply to testing data. Ok, ...
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Preparing new samples for ML classifier with the same encoders

I was wondering what's the best way to preprocess new samples for my ML classifier. I have a raw data with about 3000 samples. I'm preprocessing it with some LabelEncoders and TargetEncdoders for ...
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Using pipelines with a cross validation of several models in scikit-learn

Is there a simple way to cross-validate several models using sklearn pipelines?
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322 views

sklearn FeatureUnion vs ColumnTransformer

I am trying to build a sklearn pipeline which does different transformations on numerical data, and different transformation on categorical data. In the process, I compare the results from ...
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Data sharing between Custom Tranformer and estimator in pyspark

Using Titanic Dataset for classification. Created custom Estimator and transformer for pipeline. some of logical operation need to be done in fit() method and data ...
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1answer
73 views

Combining scaling, dimensionality reduction, prediction using sklearn pipeline

I would like to use a sklearn pipeline doing this : ( - ) scale the data ( StandardScaler ) ( - ) reduce dimensionality ( PCA ) ( - ) make a prediction with GradientBoostingRegressor() and ...
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Model ensemble with Spark or Scikit Learn

I am using Spark MLLib to make prediction and I would like to know if it is possible to create your custom Estimators. Here is a reproducible of what I would like my model to do with the Spark api <...
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178 views

sklearn predict: IndexingError: ('Too many indexers', 'occurred at index <name>')

The goal of what I'm trying to accomplish here is to have the output contain all of the use_cols but the model only be built to calculate on categorical_features. The output will then be used to ...
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52 views

Best Data Science & Machine Learning Conferences 2019? [closed]

What are the best data science conferences you have attended? I am looking for a conference that will help me further develop my Data Science and Machine Learning competencies. Topics that are ...
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How does “sameModel” mean in Spark ML Pipeline, (Section: Example: Pipeline), from the docs?

I'm looking at the Spark ML docs in scala for Section: Example Pipeline https://spark.apache.org/docs/latest/ml-pipeline.html#example-pipeline. From the example, the model is fit using a pipeline (...
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Which design pattern is better for data pipelines: batches or one at a time?

I come from a software engineering background and have a firm knowledge of best design patterns in that world, but with data science I feel like I'm making elementary design pattern mistakes. One ...
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What is the meaning of the term “pipeline” within data science?

Note: this question was asked and removed just before I posted my answer below, so am repeating the general idea here People often refer to pipelines when talking about models, data and even layers ...