Top-Down Investment Strategy Optimization with Time Series Forecasting

Data Analysis: Merge, Impute, and Interpret

Evaluates 5 methods (Linear Regression, KNN, Mean/Median Imputation, List-wise Deletion, Hot Deck) for imputing missing data in C. Identifies best method for 3 datasets, analyzing strengths and weaknesses.

Multi-class classification model to predict outcomes of cirrhosis patients using machine learning

Apply unsupervised learning techniques to identify customers segments.

analysing missing data handling methods with text-mining

Code for Master's Thesis Data Science & Society

Final project for the 2022 Python Programming Course (Madrid's Employment Agency)

EDI uses two layers/steps of imputation namely the Early-Imputation step and the Advanced-Imputation step.

Numerical data imputation methods for extremely missing data contexts

A literature review exploring how missing data was handled across the pipeline of commonly used UK clinical prediction models

Feature engineering is the process of converting raw data into a more accessible format, optimizing it for effective utilization in machine learning models.

SiMI imputes numerical and categorical missing values by making an educated guess based on records that are similar to the record having a missing value. Using the similarity and correlations, missing values are then imputed. To achieve a higher quality of imputation some segments are merged together using a novel approach.

Data Manipulation of Biopic Dataset

My Data Cleaning Library

MLimputer: Missing Data Imputation Framework for Supervised Machine Learning

Data Analysis Project using Python(Numpy, Pandas, Seaborn, matplotlib)

A multi-view panorama of Data-Centric AI: Techniques, Tools, and Applications (ECAI Tutorial 2024)

Implementation of Missing Imputation algorithms for Incomplete tabular data with PyTorch.

kDMI employs two levels of horizontal partitioning (based on a decision tree and k-NN algorithm) of a data set, in order to find the records that are very similar to the one with missing value/s. Additionally, it uses a novel approach to automatically find the value of k for each record.