# Machine Learning and Data Classification

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/machine-learning-and-data-classification/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the challenges and techniques for learning with noisy labels in machine learning, including methods for hyperparameter optimization, instance selection, robust learning, and automated machine learning. It also explores the use of meta-learning and deep neural networks in handling noisy label problems, particularly in the context of classification tasks and learning from positive and unlabeled data. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | t12535 |
| Works | 57 |

## Topic papers all

Showing 15 of 57.

- [Explainable artificial intelligence: a comprehensive review](https://scholariq.org/papers/explainable-artificial-intelligence-a-comprehensive-review/)
- [Applications of Deep Learning and Reinforcement Learning to Biological Data](https://scholariq.org/papers/applications-of-deep-learning-and-reinforcement-learning-to-biological-data/)
- [Flexible Imputation of Missing Data](https://scholariq.org/papers/flexible-imputation-of-missing-data/)
- [Performance Analysis of Google Colaboratory as a Tool for Accelerating Deep Learning Applications](https://scholariq.org/papers/performance-analysis-of-google-colaboratory-as-a-tool-for-accelerating-deep/)
- [Extracting Tree-Structured Representations of Trained Networks](https://scholariq.org/papers/extracting-tree-structured-representations-of-trained-networks/)
- [Characterizing concept drift](https://scholariq.org/papers/characterizing-concept-drift/)
- [CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise](https://scholariq.org/papers/cleannet-transfer-learning-for-scalable-image-classifier-training-with-label/)
- [Study quality assessment tools](https://scholariq.org/papers/study-quality-assessment-tools/)
- [Using Sampling and Queries to Extract Rules from Trained Neural Networks](https://scholariq.org/papers/using-sampling-and-queries-to-extract-rules-from-trained-neural-networks/)
- [Born Again Neural Networks](https://scholariq.org/papers/born-again-neural-networks-2/)
- [Ensembles of Learning Machines](https://scholariq.org/papers/ensembles-of-learning-machines/)
- [Using neural networks for data mining](https://scholariq.org/papers/using-neural-networks-for-data-mining/)
- [A survey on statistical methods for health care fraud detection](https://scholariq.org/papers/a-survey-on-statistical-methods-for-health-care-fraud-detection/)
- [Database Meets Deep Learning](https://scholariq.org/papers/database-meets-deep-learning/)
- [Artificial Intelligence Technique for Gene Expression by Tumor RNA-Seq Data: A Novel Optimized Deep Learning Approach](https://scholariq.org/papers/artificial-intelligence-technique-for-gene-expression-by-tumor-rna-seq-data-a/)

## Topic primary papers

- [Applications of Deep Learning and Reinforcement Learning to Biological Data](https://scholariq.org/papers/applications-of-deep-learning-and-reinforcement-learning-to-biological-data/)
- [Flexible Imputation of Missing Data](https://scholariq.org/papers/flexible-imputation-of-missing-data/)
- [CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise](https://scholariq.org/papers/cleannet-transfer-learning-for-scalable-image-classifier-training-with-label/)
- [Study quality assessment tools](https://scholariq.org/papers/study-quality-assessment-tools/)
- [Ensemble genetic and CNN model-based image classification by enhancing hyperparameter tuning](https://scholariq.org/papers/ensemble-genetic-and-cnn-model-based-image-classification-by-enhancing/)
- [RETRACTED ARTICLE: A taxonomy on impact of label noise and feature noise using machine learning techniques](https://scholariq.org/papers/retracted-article-a-taxonomy-on-impact-of-label-noise-and-feature-noise-using/)
- [Feature selection for distance-based regression: An umbrella review and a one-shot wrapper](https://scholariq.org/papers/feature-selection-for-distance-based-regression-an-umbrella-review-and-a-one/)
- [Classification of pancreas tumor dataset using adaptive weighted k nearest neighbor algorithm](https://scholariq.org/papers/classification-of-pancreas-tumor-dataset-using-adaptive-weighted-k-nearest/)
- [Meta-knowledge guided Bayesian optimization framework for robust crop yield estimation](https://scholariq.org/papers/meta-knowledge-guided-bayesian-optimization-framework-for-robust-crop-yield/)
- [Utilizing Random Forests for High-Accuracy Classification in Medical Diagnostics](https://scholariq.org/papers/utilizing-random-forests-for-high-accuracy-classification-in-medical-diagnostics/)
- [Rethinking Learning Rate Tuning in the Era of Large Language Models](https://scholariq.org/papers/rethinking-learning-rate-tuning-in-the-era-of-large-language-models-2/)
- [MLP-GNAS: Meta-learning-based predictor-assisted Genetic Neural Architecture Search system](https://scholariq.org/papers/mlp-gnas-meta-learning-based-predictor-assisted-genetic-neural-architecture/)
- [Unbiased Isotonic Regression Tree for Discovering Hidden Heterogeneity in Monotonicity Constraints](https://scholariq.org/papers/unbiased-isotonic-regression-tree-for-discovering-hidden-heterogeneity-in/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.