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Proprietary software for viewing and editing PDF documents. pdftk: GNU GPL/Proprietary: command-line tools to manipulate, edit and convert documents; supports filling of PDF forms with FDF/XFDF data. PDF-XChange Viewer: Freeware: Freeware PDF reader, tagger, editor (simple editions) and converter (free for non-commercial uses).
Rule-based machine learning (RBML) is a term in computer science intended to encompass any machine learning method that identifies, learns, or evolves 'rules' to store, manipulate or apply. [ 1 ] [ 2 ] [ 3 ] The defining characteristic of a rule-based machine learner is the identification and utilization of a set of relational rules that ...
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]
FileHippo is a software downloading website that offers computer software for Windows. The website has sections listing most recently updated programs and most popular downloads, organised by category, with program information and link. Registration is not required in this website. FileHippo does not accept software submissions from publishers. [1]
Machine learning (ML) is a subfield of artificial intelligence within computer science that evolved from the study of pattern recognition and computational learning theory. [1] In 1959, Arthur Samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed". [ 2 ]
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
Supervised learning involves learning from a training set of data. Every point in the training is an input–output pair, where the input maps to an output. The learning problem consists of inferring the function that maps between the input and the output, such that the learned function can be used to predict the output from future input.
Feature learning is intended to result in faster training or better performance in task-specific settings than if the data was input directly (compare transfer learning). [1] In machine learning (ML), feature learning or representation learning [2] is a set of techniques that allow a system to automatically discover the representations needed ...