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  2. Logistic regression - Wikipedia

    en.wikipedia.org/wiki/Logistic_regression

    The goal of logistic regression is to use the dataset to create a predictive model of the outcome variable. As in linear regression, the outcome variables Y i are assumed to depend on the explanatory variables x 1,i... x m,i. Explanatory variables. The explanatory variables may be of any type: real-valued, binary, categorical, etc.

  3. RevoScaleR - Wikipedia

    en.wikipedia.org/wiki/RevoScaleR

    The package is mostly meant to be used with a SQL server or other remote machines. To fully leverage the abstractions it uses to process a large dataset, one needs a remote server and non-Express free edition of the package. It cannot be easily installed such as by running "install.packages("RevoScaleR")" like most open source R packages.

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

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

    Provides classification and regression datasets in a standardized format that are accessible through a Python API. Metatext NLP: https://metatext.io/datasets web repository maintained by community, containing nearly 1000 benchmark datasets, and counting. Provides many tasks from classification to QA, and various languages from English ...

  5. One in ten rule - Wikipedia

    en.wikipedia.org/wiki/One_in_ten_rule

    In statistics, the one in ten rule is a rule of thumb for how many predictor parameters can be estimated from data when doing regression analysis (in particular proportional hazards models in survival analysis and logistic regression) while keeping the risk of overfitting and finding spurious correlations low. The rule states that one ...

  6. Multinomial logistic regression - Wikipedia

    en.wikipedia.org/.../Multinomial_logistic_regression

    Multinomial logistic regression is known by a variety of other names, including polytomous LR, [2] [3] multiclass LR, softmax regression, multinomial logit (mlogit), the maximum entropy (MaxEnt) classifier, and the conditional maximum entropy model.

  7. Logistic model tree - Wikipedia

    en.wikipedia.org/wiki/Logistic_model_tree

    In computer science, a logistic model tree (LMT) is a classification model with an associated supervised training algorithm that combines logistic regression (LR) and decision tree learning. [ 1 ] [ 2 ]

  8. List of datasets in computer vision and image processing

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

    The dataset is labeled with semantic labels for 32 semantic classes. over 700 images Images Object recognition and classification 2008 [56] [57] [58] Gabriel J. Brostow, Jamie Shotton, Julien Fauqueur, Roberto Cipolla RailSem19 RailSem19 is a dataset for understanding scenes for vision systems on railways. The dataset is labeled semanticly and ...

  9. Conditional logistic regression - Wikipedia

    en.wikipedia.org/.../Conditional_logistic_regression

    Conditional logistic regression is available in R as the function clogit in the survival package. It is in the survival package because the log likelihood of a conditional logistic model is the same as the log likelihood of a Cox model with a particular data structure. [3]