Data Science Notebook on a Classification Task, using sklearn and Tensorflow.
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Updated
Dec 21, 2021 - Jupyter Notebook
Data Science Notebook on a Classification Task, using sklearn and Tensorflow.
center loss for face recognition
Display and analyze ROC curves in R and S+
PyTorch-Based Evaluation Tool for Co-Saliency Detection
Hyperspectral image Target Detection based on Sparse Representation
This repo contains regression and classification projects. Examples: development of predictive models for comments on social media websites; building classifiers to predict outcomes in sports competitions; churn analysis; prediction of clicks on online ads; analysis of the opioids crisis and an analysis of retail store expansion strategies using…
Optimal cutpoints in R: determining and validating optimal cutpoints in binary classification
The data is related with direct marketing campaigns (phone calls) of a Portuguese banking institution. The classification goal is to predict if the client will subscribe a term deposit.
Machine learning utility functions and classes.
With unbalanced outcome distribution, which ML classifier performs better? Any tradeoff?
Measure and visualize machine learning model performance without the usual boilerplate.
Detecting hate speech using the spoken content of videos using Machine Learning
Assignment-06-Logistic-Regression. Output variable -> y y -> Whether the client has subscribed a term deposit or not Binomial ("yes" or "no") Attribute information For bank dataset Input variables: # bank client data: 1 - age (numeric) 2 - job : type of job (categorical: "admin.","unknown","unemployed","management","housemaid","entrepreneur","st…
Predicting the price of a football player using Machine Learning Algorithms
Detecting credit card fraud detection. Selecting an optimum threshold with analysis of confusion matrix and ROC curce
A light and flexible R package to evaluate GWAS-based gene prioritization methods for complex traits.
Tool demonstrating building credit risk models
L2 Orthonormal Face Recognition Performance under L2 Regularization Term
ML/CNN Evaluation Metrics Package
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