classification

How to Fine-tune Model Thresholds with Yellowbrick’s ROC-AUC Visualization

The key challenge lies in finding the right balance: How cautious should our model be when making classifications?

Building classifiers with biased classes: AdaSampling comes to the rescue

An algorithmic approach to clean up your dataset and sharpen class assignments.

Recipe Cuisine Classification

BERT Transformer & Food-Drug Negative Interactions

Precision, Recall, and F1 Score of Multiclass Classification — Learn in Dep

Manual Calculation From a Confusion Matrix and the Syntax of sklearn Library

Cross-Topic Argument Mining: Learning How to Classify Texts

Classifying cross-topic natural language texts based on their argumentative structure using deep learning

Text Classifier Algorithms in Machine Learning – Stats and Bots

Hierarchical Classification – a useful approach when predicting thousands o

Traditionally, most of the multi-class classification problems (i.e. problems where you want to predict where a given sample falls into, from a set of possible results) focus on a small number of possible predictions.

Visualizing classifier thresholds | R-bloggers

Lately I’ve been thinking a lot about the connection between prediction models and the decisions that they influence. There is a lot of theory around this, but communicating how the various pieces all fit together with the folks who will use and be impacted by these decisions can be challenging. One of the important conceptual pieces […]

delgado14a.pdf 📄

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classification