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Results tagged with machine-learning
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user 111822
Machine Learning is a subfield of computer science that draws on elements from algorithmic analysis, computational statistics, mathematics, optimization, etc. It is mainly concerned with the use of data to construct models that have high predictive/forecasting ability. Topics include modeling building, applications, theory, etc.
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votes
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68
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Data snooping and information leakage?
I need help in deciding whether my below implementation imposes data snooping bias and information leakage from the test/evaluation set to the train set.
I have a text corpus of 10k+ short online comm …
- 299
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votes
1
answer
1k
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Semi-supervised classification with SelfTrainingClassifier: no training after calling fit()
I am practicing semi-supervised learning, at the moment experimenting with sklearn.semi_supervised.SelfTrainingClassifier. I found a dataset for multiclass classification (tweet sentiment classificati …
- 299
0
votes
1
answer
420
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Accessing regression coefficients when using MultiOutputRegressor
I am working on a multioutput (nr. targets: 2) regression task. The original data has a huge dimensionality (p>>n, i.e. there are far more predictors than observations), hence for the baseline models …
- 299
1
vote
1
answer
290
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How to combine preprocessor/estimator selection with hyperparameter tuning using sklearn pip...
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 as heterogeneous data, in the latte …
- 299
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2
answers
680
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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 …
- 299
5
votes
1
answer
292
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Visualizing effect of regularization for linear regression problem
I wanted to put together an example notebook to demonstrate how regularization makes an impact for such a simple model as a simple linear regression. When executing the below script though, I notice t …
- 299
4
votes
1
answer
2k
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Choose ROC/AUC vs. precision/recall curve?
I am trying to get a clear understanding on various classification metrics, including knowing when to choose ROC/AUC as opposed to opting for the Precision/Recall curve.
I am reading Aurélien Géron's …
- 299
1
vote
1
answer
146
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Trouble understanding regression line learned by SGDRegressor
I am working on a demonstration notebook to better understand online (incremental) learning. I read in sklearn documentation that the number of regression models that support online learning via the p …
- 299
3
votes
2
answers
2k
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Uncertainty about shape of ROC curve
I am working on a binary classification and the plotted ROC curves that I am using for evaluation together with AUC, have seemed strange to me. Here is an example.
I understand that ROC is a visual r …
- 299
4
votes
Uncertainty about shape of ROC curve
Oops. I found the reason!
The shape of ROC returned by the roc_curve depends on the number of unique values that are input to roc_curve. In my case I was getting only 3 points on the ROC curve. The mi …
- 299
0
votes
1
answer
658
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Custom vectorizer transformer in sklearn with cross validation
I created a custom transformer class called Vectorizer() that inherits from sklearn's BaseEstimator and TransformerMixin classes. The purpose of this class is to provide vectorizer-specific hyperparam …
- 299
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Using KerasClassifier for training neural network
I managed to solve it!
The core mistake was that scikeras doesn't accept non-numerical input. As such I needed to resort to a workaround by eliminating the text preprocessing steps from my custom buil …
- 299
0
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1
answer
2k
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Using KerasClassifier for training neural network
I created a simple neural network for binary spam/ham text classification using pretrained BERT transformer. The current pure-keras implementation works fine. I wanted however to plot certain metrics …
- 299