ppmi

Four word embedding models implemented in Python. Supporting arbitrary context features

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Analysis of Parkinson's Progressive Markers Initiative Data

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🧮 Python package to construct word embeddings for small data using PMI and SVD

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• Python

An implementation of (Chambers and Jurafsky, 2008), using updated machine learning models, and different training data domains for an independent study at the University of Pennsylvania.

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• Python

意味表現学習

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In this paper we compare and evaluate two simple embedding models which can be constructed directly from a given co-occurrence matrix extracted from Twitter data; Positive Pointwise Mutual Information (PPMI), and Hellinger Principal Component Analysis (H-PCA). For each embedding model we consider three alternative metrics for word similarity: co…

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Parkinson's Progression Marker Initiative data science challenge, 2016

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• R

The project strives to predict the risk of Parkinson's Disease progression in the patient based on the evaluation of baseline motor and non-motor symptoms of the patients via machine learning approach.

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Effects of MRI scanner manufacturers in classification tasks with deep learning models

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• R

Construct Word Embeddings with PPMI & SVD

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• Python

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BPF Parkinson's disease validation — PPMI expression, genotype, and prodromal detection (AUC 0.766)

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Análise empírica de acórdãos do STF sobre desinformação e os atos antidemocráticos de 8 de janeiro de 2023: pipeline reprodutível com MCDA/WSM, BM25, TF-IDF/cosseno, seleção estratificada, nuvem de palavras e heatmap PPMI.

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In this assignment I will explore different kind of encoding techniques such as co-occurrence matrix, sparse representations via PPMI weighting, pre-trained dense word embeddings, ecc...

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This repository contains two implementations of an NLP document query system that processes PDF documents and ranks them based on relevance to user queries.

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My thesis work. Data processing on Google Drive. Here are only scripts and key findings.

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Turn documents into vectors by decomposing a PPMI cooccurence matrix.

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• HTML

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This project focuses on text mining "The Big Bang Theory" scripts, covering 10 seasons. Participants preprocess character dialogues, analyzing sentence/word counts, noun/person name mentions, important words per episode/season, and word co-occurrence. (Part of Evaluation of Text Mining-KUL [G00C8a])

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