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  2. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Multiple recordings of people with and without Parkinson's Disease. Voice features extracted, disease scored by physician using unified Parkinson's disease rating scale. 1,040 Text Classification, regression 2013 [122] [123] B. E. Sakar et al. Spoken Arabic Digits Spoken Arabic digits from 44 male and 44 female.

  3. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    Skin Segmentation Dataset Randomly sampled color values from face images. B, G, R, values extracted. 245,057 Text Segmentation, classification 2012 [103] [104] R. Bhatt. Bosphorus 3D Face image database. 34 action units and 6 expressions labeled; 24 facial landmarks labeled. 4652 Images, text Face recognition, classification 2008 [105] [106]

  4. Mathematical modelling of infectious diseases - Wikipedia

    en.wikipedia.org/wiki/Mathematical_modelling_of...

    If a model makes predictions that are out of line with observed results and the mathematics is correct, the initial assumptions must change to make the model useful. [ 13 ] Rectangular and stationary age distribution , i.e., everybody in the population lives to age L and then dies, and for each age (up to L ) there is the same number of people ...

  5. Kaggle - Wikipedia

    en.wikipedia.org/wiki/Kaggle

    Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.

  6. Predictive medicine - Wikipedia

    en.wikipedia.org/wiki/Predictive_medicine

    The goal of predictive medicine is to predict the probability of future disease so that health care professionals and the patient themselves can be proactive in instituting lifestyle modifications and increased physician surveillance, such as bi-annual full body skin exams by a dermatologist or internist if their patient is found to have an increased risk of melanoma, an EKG and cardiology ...

  7. Symbolic regression - Wikipedia

    en.wikipedia.org/wiki/Symbolic_regression

    In other words, it attempts to discover both model structures and model parameters. This approach has the disadvantage of having a much larger space to search, because not only the search space in symbolic regression is infinite, but there are an infinite number of models which will perfectly fit a finite data set (provided that the model ...

  8. Uplift modelling - Wikipedia

    en.wikipedia.org/wiki/Uplift_modelling

    Uplift modelling uses a randomised scientific control not only to measure the effectiveness of an action but also to build a predictive model that predicts the incremental response to the action. The response could be a binary variable (for example, a website visit) [ 1 ] or a continuous variable (for example, customer revenue). [ 2 ]

  9. Artificial intelligence in healthcare - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence_in...

    Artificial intelligence in healthcare is the application of artificial intelligence (AI) to analyze and understand complex medical and healthcare data. In some cases, it can exceed or augment human capabilities by providing better or faster ways to diagnose, treat, or prevent disease.