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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Data Transformation Pipeline Issue on Flight Fare Prediction End-to-End Machine Learning Project

I am following the process shown on Wine Quality Prediction End-to-End ML Project on Krish Naik's YouTube channel to do a Flight Fare Prediction Project. I am facing an issue with Data Transformation ...
Md. Ehsanul Haque Kanan's user avatar
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How to handle multiple training jobs in AWS Sagemaker Pipelines?

I am trying to create a pipeline for training an image dataset via Sagemaker Pipelines. Based on the examples I understood that for all distinct stages like data preparation, model training, ...
Mimansa Maheshwari's user avatar
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How does TensorFlow method tf.data.Dataset.reduce() work?

I was trying to compute the mean of the images that I fetched from a GCS bucket using TensorFlow's tf.data input pipeline. For this, I came across two methods: ...
Harsh Khare's user avatar
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Create a TensorFlow Input pipeline from GCS Bucket?

I wish to generate a TensorFlow input pipeline (i.e. tf.data pipeline) for an image classification project. The images stored in a GCS bucket having access controls and is not publicly accessible. And ...
Harsh Khare's user avatar
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Data transformation pipeline error

When I'm making data transformation pipeline on a dataset I keep getting error as " all the input array dimensions except for concatenation axis must match exactly, but along dimension 0, the ...
Amy's user avatar
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Visualize Catboost and XGBoost training process + Cross Validation

I want to optimize Catboost and XGBoost models and visualize this process such that: Use 3-fold cross-validation Use my own pre-processing pipeline (Missing value imputation, over- or undersampling) ...
Ars ML's user avatar
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Read from database every time a new record goes through a Spark pipeline

I'm using Spark to filter and transform every new record that goes through a data stream, the problem is that for each new record I need to read a table from a Cassandra database in order to have the ...
José Luis Benitez's user avatar
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191 views

What is the best\correct data split approach over time-series data to compare performance of forecasting future data among ML and DL regressors?

Let's say I have dataset contains a timestamp (non-standard timestamp column without datetime format) as a single feature and count as Label/target to predict ...
Mario's user avatar
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Sklearn pipelines, applying transformations to feature engineered columns in previous steps

I am working on a sklearn pipeline for my binary classification problem. The pipeline should perform typical things like downcasting data types, scaling numerical values, one-hot and ordinal encoding ...
fendrbud's user avatar
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73 views

ı am writing data process pipeline with luigi but ı get error

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Vahşi Bozkırlı's user avatar
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Memory Error when loading a txt file for an ML model

I am trying to run the Python code below: ...
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Creating new features as linear combination of others as part of a scikit-learn pipeline?

I have a number of raw features that go into a scikit-learn model. I've already got a number of preprocessing steps (such as PolynomialFeatures) that creates additional features as part of my pipeline....
gammapoint's user avatar
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Optimization of the entire model development process

I want to perform a global optimization of the entire model development pipeline. I have several stages of development, each of which can be performed automatically: preprocessing, removal of outliers/...
Andrew's user avatar
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How do SciKit-Learn Pipelines pass Data between Steps?

I would like to create some Custom Transformers and incorporate them in a SciKit-Learn Pipeline. I'd like to pass more than just a Dataframe between the transformer ...
Connor's user avatar
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Does Scikit-Learn's OneHotEncoder make all Columns Categorical?

I've been using Scikit-Learn's OneHotEncoder to turn categorical data into binary columns, however, it seems that fitting ...
Connor's user avatar
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How to solve mismatched code dependency issues between two or more different ML models/structures/frameworks?

I'm fairly new to machine learning. Currently I am trying to build a pipeline that uses two established NLP models. One is BERT that is fairly easy to load and quite structured. Another is FLAIR which ...
Rafsan Ahmed's user avatar
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How to make a pipeline for Videos Dataset for TensorFlow [Sequence Matters] & train Model Effectively with Low Memory System

I am working on a Deep Learning project and I am facing an issue with the size of the dataset. I want to make a pipeline for video dataset [Sequence Matters]. Because if I try the load the whole ...
Sharjeel M.'s user avatar
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1 answer
453 views

Combining sklearn pipelines with different output shape

As part of a data preprocessing step, I'm trying to create a "master pipeline" from two separate pipelines, one for numerical features and one for datetime features. The numerical pipeline ...
fendrbud's user avatar
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Sklearn pipeline and custom transformers to remove specific value from columns

I'm trying to use sklearn pipelines and custom transformers to do outlier removal. What I want to do is identify outliers using an IQR-filter, set the outlier values to 'OUTLIER' (not NaN), and then ...
fendrbud's user avatar
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SkLearn DecisionTree doesn't include numerical variables after one hot encoding pipeline

I'm trying to fit a dataframe with SkLearn DecisionTree with the following code. But I get a error Length of feature_names, 9 does not match number of features, 8. ...
esokumamon's user avatar
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1k views

Error getting prediction explanation using shap_values when using scikit-learn pipeline?

I am building an NLP model to predict language type (C/C++/C#/Python...) for a given code. Now I need to provide an explanation for my model prediction. For example the following user_input is written ...
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Need an example of a custom class whose instance is fed to sklearn Pipeline / make_pipeline to use with GridSearchCV

According to sklearn.pipeline.Pipeline documentation, the class whose instance is a pipeline element should implement fit() and transform(). I managed to create a custom class that has these methods ...
James's user avatar
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I cannot work out the benefits of a pipeline over a linear sequence of code instructions

I've looked at quite a number of how to 'create a pipeline' instructions, but I have yet to see an explanation of the benefits over what I am showing below. To keep my example code agnostic I'll use ...
ThomasAJ's user avatar
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2 answers
501 views

Dynamic creation of sklearn pipeline

I am trying to create an automatic pipeline builder functionality that takes into account a large set of conditions such as the existence of missing values, the scale of numerical features, etc., and ...
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How to retrain sklearn pipeline with new data?

I have trained and saved a data processing pipeline and an LGBM regressor on 3 months of historical data. Now I know that I can retrain the LGBM regressor on new data every day by passing my trained ...
shobhit_kulshreshtha's user avatar
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715 views

Retrieving the ordinal encoding of a variable after it's placed in a pipeline/columntransformer

I am applying ordinal encoding to a dataset through a column transformer - how can I retrieve the ordinal encoding of a feature (e.g. Area)? ...
lostwanderer's user avatar
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155 views

Does sklearn.pipeline have a single mechanism for cross-validation regardless of model API?

With a single standard interface (sklearn.pipeline) on top of different regressors, how do I use cross-validation? The example below uses two regressors with different internal cross-validation ...
user5406764's user avatar
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493 views

Custom vectorizer transformer in sklearn with cross validation

I created a custom transformer class called Vectorizer() that inherits from sklearn's ...
lazarea's user avatar
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1 answer
167 views

Explaining the logic behind the pipe_line method for cross-validation of imbalance datasets

Reading the following article: https://kiwidamien.github.io/how-to-do-cross-validation-when-upsampling-data.html There is an explanation of how to use ...
PwNzDust's user avatar
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1 answer
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How to combine preprocessor/estimator selection with hyperparameter tuning using sklearn pipelines?

I'm aware of how to use sklearn.pipeline.Pipeline() for simple and slightly more complicated use cases alike. I know how to set up pipelines for homogeneous as well ...
lazarea's user avatar
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129 views

Custom preprocessing using piplines

I have searched a lot for this issue but unfortunately came up with nothing. Usually in a ML model, during preprocessing, we use Pipelines and ...
spectre's user avatar
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ColumnTransformer worse performance than sklearn pipeline

I have an (unbalanced , binary data) pipeline model consisting of two pipelines (preprocessing and the actual model). Now I wanted to include SimpleImputer into my ...
corianne1234's user avatar
1 vote
2 answers
535 views

Deep Neural Network Model in sklearn Pipeline

Is it possible to add a deep neural network model as the estimator/model in an sklearn Pipeline? or is it only possible for ML models as the estimator. For example, ...
DataPlug's user avatar
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Shap after scikit pipeline - feature name

I'm using pipeline to transform data and predict model and I want to apply SHAP after that. However, when I apply it, it returns SHAP chart just fine, but the name of the feature are like feature 1, ...
rebar's user avatar
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2 votes
1 answer
4k views

How can I get the dataframe after scikit pipeline?

I'm making many data transformations and fitting a model using scikit pipeline, but I need to extract X_train and X_test right after transformations (imputer, encoding, etc) in order to use it for ...
rebar's user avatar
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1 answer
47 views

when I only give command 'fit', my class does 'transform' too

I have created 2 classes, first of which is: ...
greeksalad's user avatar
4 votes
1 answer
217 views

What can I do when my test and validation scores are good, but the submission is terrible?

This is a very broad question, I understand and I'm totally fine if someone believes it's not appropriate to do it. But it's killing me not to understand this... Here's the thing, I'm doing a machine ...
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2 answers
7k views

AttributeError: 'numpy.ndarray' object has no attribute 'fit' [closed]

I am relatively new to ML and in the process of learning pipelines. I am creating a pipeline of custom transformers and get this error: AttributeError: 'numpy.ndarray' object has no attribute 'fit'. ...
nagesh hatti's user avatar
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1 answer
2k views

How to get column names after One Hot Encoding when using Pipelines?

I am using Pipeline and ColumnTransformer to preprocess the data. Basically I am using them to impute null values, scale the ...
spectre's user avatar
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1 vote
2 answers
106 views

unsupervised anomaly detection for univariate fast frequency time series data?

I have a univariate time series (there is a value for each time sampling) (sampling time: 66.66 micro second, number of samples/sampling time=151) coming from a scala customer This time series ...
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determining size of batch, time of sending and memory in to send from scala to ML section

I have a time series (sampling time: 66.66 micro second, number of samples/sampling time=151), I would like to determine some anomalies in them, the inputs are made by scala customer message bus. ...
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Pipelines with categorical and nan values

I am trying a Regression model on a dataset which has categorical and numerical variables along with nan values. I want to use Pipelines for imputation and encoding purposes. Now I have a few ...
spectre's user avatar
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1 vote
1 answer
138 views

Alternative to EC2 for running ML batch training jobs on AWS

We are building an ML pipeline on AWS, which will obviously require some heavy-compute components including preprocessing and batch training. Most the the pipeline is on Lambda, but Lambda is known to ...
Cybernetic's user avatar
1 vote
0 answers
127 views

Data Pipeline Best Practices

I am looking more for concepts or pointed in the right direction for best practices for a project I am working on. I am currently playing around with Luigi for a data pipeline. I followed the tutorial ...
ghawes's user avatar
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2 votes
1 answer
441 views

TPOT machine learning

I trained a regression TPOT algorithm on Google Colab, where the output of the TPOT process is some boiler plate Python code as shown below. ...
bbartling's user avatar
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24 views

Working with others: Tidy data vs Pretty data [closed]

When working with someone whose background and skill level in data work may not be strong, how do you best make the argument for tidy data over "pretty" data? There are notes of what I want ...
Rob Creel's user avatar
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1 answer
683 views

How to use SMOTE in Stacking in SKLearn?

I have a data set X,y and split them to train and test data. ...
Amin's user avatar
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4 votes
1 answer
9k views

Why GridSearchCV returns nan?

I am using gridsearchcv to tune the parameters of my model and I also use pipeline and cross-validation. When I run the model to tune the parameter of XGBoost, it returns ...
Amin's user avatar
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1 answer
262 views

cost-complexity-pruning-path with pipeline

I'm using Kaggle's titanic set. I'm using pieplines and I'm trying to prune my decision tree and for that I want the cost_complexity_pruning_path. The last line of code produces the error: ...
user5744148's user avatar
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1k views

How to remove features from a sklearn pipeline after it has already been fitted?

Background: I have created a basic modeling workflow in sklearn that utilizes sklearn's pipeline object. There are some preprocessing steps within the pipeline, and the last step of the pipeline is to ...
DataScienceRick's user avatar