Search Results for "python feature selection" - Page 12
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Showing 602 open source projects for "python feature selection"
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Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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ToMe (Token Merging)
A method to increase the speed and lower the memory footprint
ToMe (Token Merging) is a PyTorch-based optimization framework designed to significantly accelerate Vision Transformer (ViT) architectures without retraining. Developed by researchers at Facebook (Meta AI), ToMe introduces an efficient technique that merges similar tokens within transformer layers, reducing redundant computation while preserving model accuracy. This approach differs from token pruning, which removes background tokens entirely; instead, ToMe merges tokens based on feature... -
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XLabel
XLabel: An Explainable Data Labeling Assistant
XLabel is an open-source Streamlit app that takes an explainable machine-learning approach to visual-interactive data labeling. Predict the most probable labels using Explainable Boosting Machine (EBM). Show the contributions of each feature towards the predicted labels. Provide an option to write the labels directly into the data file (use XLabel.py) or save them in a separate file (use XLabelDL.py) Support data with multiple labels and multiple classes. Support data with missing values... -
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HomeworkHelper
Homework Helper: Organize tasks, meet deadlines. Ideal for ADHD
Homework Helper is a comprehensive and user-friendly application designed to assist students in effectively managing their homework and assignments. It provides a convenient and organized platform to keep track of upcoming tasks, due dates, subjects, and associated details. Developed with a focus on simplicity and usability, Homework Helper aims to support students, including those with ADHD or individuals struggling with task management, in staying organized and achieving academic success.... -
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auto-sklearn
Automated machine learning with scikit-learn
auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. auto-sklearn frees a machine learning user from algorithm selection and hyperparameter tuning. It leverages recent advantages in Bayesian optimization, meta-learning and ensemble construction. Auto-sklearn 2.0 includes latest research on automatically configuring the AutoML system itself and contains a multitude of improvements which speed up the fitting the AutoML system.... -
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TradeMaster
TradeMaster is an open-source platform for quantitative trading
TradeMaster is a first-of-its-kind, best-in-class open-source platform for quantitative trading (QT) empowered by reinforcement learning (RL), which covers the full pipeline for the design, implementation, evaluation and deployment of RL-based algorithms. TradeMaster is composed of 6 key modules: 1) multi-modality market data of different financial assets at multiple granularities; 2) whole data preprocessing pipeline; 3) a series of high-fidelity data-driven market simulators for mainstream... -
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Merlion
A Machine Learning Framework for Time Series Intelligence
Merlion is a Python library for time series intelligence. It provides an end-to-end machine learning framework that includes loading and transforming data, building and training models, post-processing model outputs, and evaluating model performance. It supports various time series learning tasks, including forecasting, anomaly detection, and change point detection for both univariate and multivariate time series. This library aims to provide engineers and researchers a one-stop solution to... -
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DDoS/Dos Attack Simulator
Distributed Denial of Service Attack Simulator
DDoS/DoS Attack Simulator is powerful Python-based software used for attacking servers, hosts, and websites using traffic. It disrupts the normal traffic of a targeted server, service, or network by overwhelming the target or its surrounding infrastructure with a flood of Internet traffic. A server that does not have protection against it can experience extremely slow performance due to all of the traffic it sends. -
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FastAPI CRUD Router
A dynamic FastAPI router that automatically creates CRUD routes
Tired of rewriting generic CRUD routes? Need to rapidly prototype a feature for a presentation or a hackathon? Thankfully, fastapi-crudrouter has your back. As an extension to the APIRouter included with FastAPI, the FastAPI CRUDRouter will automatically generate and document your CRUD routes for you, all you have to do is pass your model and maybe your database connection. fastapi-crudrouter provides a number of features that allow you to get the most out of your automatically generated... -
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ConvNeXt V2
Code release for ConvNeXt V2 model
ConvNeXt V2 is an evolution of the ConvNeXt architecture that co-designs convolutional networks alongside self-supervised learning. The V2 version introduces a fully convolutional masked autoencoder (FCMAE) framework where parts of the image are masked and the network reconstructs the missing content, marrying convolutional inductive bias with powerful pretraining. A key innovation is a new Global Response Normalization (GRN) layer added to the ConvNeXt backbone, which enhances feature... -
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Compose
A machine learning tool for automated prediction engineering
Compose is a machine learning tool for automated prediction engineering. It allows you to structure prediction problems and generate labels for supervised learning. An end user defines an outcome of interest by writing a labeling function, then runs a search to automatically extract training examples from historical data. Its result is then provided to Featuretools for automated feature engineering and subsequently to EvalML for automated machine learning. Prediction problems are structured... -
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footswitch3
Audio Transcription software for Linux (Gstreamer) with a foot pedal
Footswitch 3 is a media player for transcribers on Linux. Written in python using the python bindings for Gstreamer it allows a transcriber to control the audio or video with a foot pedal, and includes a set of macros that integrate into LibreOffice. This allows the transcriber to control the media player from within Libreoffice as well, making it useful for those who do not yet own a foot pedal/foot switch. Control of the media player from LibreOffice can be via Hotkeys or an integrated... -
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OmicSelector
Feature selection and deep learning modeling for omic biomarker study
OmicSelector is an environment, Docker-based web application, and R package for biomarker signature selection (feature selection) from high-throughput experiments and others. It was initially developed for miRNA-seq (small RNA, smRNA-seq; hence the name was miRNAselector), RNA-seq and qPCR, but can be applied for every problem where numeric features should be selected to counteract overfitting of the models. Using our tool, you can choose features, like miRNAs, with the most significant diagnostic potential (based on the results of miRNA-seq, for validation in qPCR experiments). -
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Kanbanara
Web-based Project Management System using the Kanban methodology
Kanbanara, a web-based Project Management System, uses the Kanban methodology. Started in 2013, the product is already quite well advanced. It is written in Python 3.7+ and utilizes MongoDB and CherryPy. Its Kanban board features projects, user-definable workflow with custom states, support for epic, feature, story, enhancement, defect, task, test, bug and transient cards, global and personal WIP limits, role-based columns (Owner, Reviewer or Quality Assurance), support for ghost cards (cards on their way to you or your own cards currently being reviewed or in QA), blockable cards, hidable cards, deferable cards, 46 card styles including a customisable one, 14-day future projection, Gantt Chart andcard backdrops. ... -
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EG ClamNet Antivirus
A simple antivirus that provide a graphical interface for ClamAV
EG ClamNet Antivirus provides a graphical user interface for ClamAV Executables. EG ClamNet antivirus is simple and user friendly antivirus (currently for Windows OS ) that uses ClamAV as an internal scanning engine to detect trojans, viruses, malware and other known malicious threats. It can be installed on the existing default windows antivirus (Windows Defender) and compatible with it as extra protection. 1) Antivirus & Internet Security: EG ClamNet Antivirus is powered by ClamAV... -
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footswitch3basic
Audio Transcription software for Linux (Gstreamer) with a foot pedal
Footswitch3basic is a media player for transcribers on Linux. Written in python using the bindings for Gstreamer it allows a transcriber to control the audio or video with a foot pedal, and includes a set of macros that integrate into LibreOffice. This allows the transcriber to control the media player from within Libreoffice as well, making it useful for those who do not yet own a foot pedal/foot switch. Control of the media player from LibreOffice can be via Hotkeys or an integrated... -
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tgcf
The ultimate tool to automate custom telegram message forwarding
The ultimate tool to automate custom telegram message forwarding. Live-syncer, Auto-poster, backup-bot, cloner, chat-forwarder, duplicator, ... Call it whatever you like! tgcf is an advanced telegram chat forwarding automation tool that can fulfill all your custom needs. -
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Twinify
Privacy-preserving generation of a synthetic twin to a data set
twinify is a software package for the privacy-preserving generation of a synthetic twin to a given sensitive tabular data set. On a high level, twinify follows the differentially private data-sharing process introduced by Jälkö et al.. Depending on the nature of your data, twinify implements either the NAPSU-MQ approach described by Räisä et al. or finds an approximate parameter posterior for any probabilistic model you formulated using differentially private variational inference (DPVI).... -
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DDPM-CD
Remote sensing change detection using denoising diffusion models
This is the Pytorch implementation of Remote Sensing Change Detection using Denoising Diffusion Probabilistic Models. The generated images contain objects that we commonly see in real remote sensing images, such as buildings, trees, roads, vegetation, water surfaces, etc., demonstrating the powerful ability of the diffusion models to extract key semantics that can be further used in remote sensing change detection. We fine-tune a light-weight change detection head which takes multi-level... -
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dein.vim
Dark powered Vim/Neovim plugin manager
dein.vim is a high-performance, feature-rich plugin manager for Vim and Neovim that enables fast startup and efficient plugin loading. It supports managing plugins from GitHub and local directories, with a design that balances speed (like vim-plug) and flexibility (like NeoBundle). Active development has ceased, with only bug fixes expected going forward. Function API and familiar patterns, without commands or dependency hell. Clean asynchronous installation supported. Supports plugins from... -
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aiopg
aiopg is a library for accessing a PostgreSQL database
aiopg is an asynchronous PostgreSQL database driver for Python built on top of asyncio and psycopg2. It provides support for asynchronous query execution and connection pooling, enabling efficient, non-blocking database access in Python applications. aiopg is well-suited for web services and microservices that require concurrency without threads. -
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LSTMs for Human Activity Recognition
Human Activity Recognition example using TensorFlow on smartphone
LSTM-Human-Activity-Recognition is a machine learning project that demonstrates how recurrent neural networks can be used to recognize human activities from sensor data. The repository implements a deep learning model based on Long Short-Term Memory (LSTM) networks to classify physical activities using time-series data collected from wearable sensors. The project uses the well-known Human Activity Recognition dataset derived from smartphone accelerometer and gyroscope signals. Through the... -
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Yellowbrick
Visual analysis and diagnostic tools to facilitate ML selection
Yellowbrick extends the Scikit-Learn API to make model selection and hyperparameter tuning easier. Under the hood, it’s using Matplotlib. Yellowbrick is a suite of visual diagnostic tools called "Visualizers" that extend the scikit-learn API to allow human steering of the model selection process. In a nutshell, Yellowbrick combines scikit-learn with matplotlib in the best tradition of the scikit-learn documentation, but to produce visualizations for your machine learning workflow. -
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Emb-GAM
An interpretable and efficient predictor using pre-trained models
Deep learning models have achieved impressive prediction performance but often sacrifice interpretability, a critical consideration in high-stakes domains such as healthcare or policymaking. In contrast, generalized additive models (GAMs) can maintain interpretability but often suffer from poor prediction performance due to their inability to effectively capture feature interactions. In this work, we aim to bridge this gap by using pre-trained neural language models to extract embeddings for... -
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AWS GameKit Plugin for Unreal
The AWS GameKit Plugin for Unreal
AWS GameKit is an open-source engine integration toolkit for game developers who want to create high-quality, cloud-connected game features without the potentially steep learning curve for cloud service architecture and AWS. With AWS GameKit, you can deliver core functionality to your players with minimal effort and time by using pre-built AWS solutions for your game backend and integrating the features into your game. You can use the AWS GameKit game features as designed or as a launch pad... -
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PyTorch Transfer-Learning-Library
Transfer Learning Library for Domain Adaptation, Task Adaptation, etc.
TLlib is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms or readily apply existing algorithms. We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please...
