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The author-topic model by Rosen-Zvi et al. [13] models the topics associated with authors of documents to improve the topic detection for documents with authorship information. HLTA was applied to a collection of recent research papers published at major AI and Machine Learning venues. The resulting model is called The AI Tree.
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
Partial least squares (PLS) regression is a statistical method that bears some relation to principal components regression and is a reduced rank regression [1]; instead of finding hyperplanes of maximum variance between the response and independent variables, it finds a linear regression model by projecting the predicted variables and the observable variables to a new space of maximum ...
Uses a white box or open-box [3] model. If a given situation is observable in a model the explanation for the condition is easily explained by Boolean logic . By contrast, in a black box model, the explanation for the results is typically difficult to understand, for example with an artificial neural network .
Archival research; Case study uses different research methods (e.g. interview, observation, self-report questionnaire) with a single case or small number of cases. Computer simulation (modeling) Ethnography; Event sampling methodology, also referred to as experience sampling methodology, diary study, or ecological momentary assessment
Marketing researchers use discrete choice models to study consumer demand and to predict competitive business responses, enabling choice modelers to solve a range of business problems, such as pricing, product development, and demand estimation problems. In market research, this is commonly called conjoint analysis. [1]
The discourse about postqualitative inquiry arose from the question of “what comes next for qualitative research," [6] particularly regarding how to approach "a problem in the midst of inquiry” [7] in a way that allows new ideas to take shape from preconceived ones. St. Pierre suggested that being restricted to method conforms new research to the form of existing research, hindering ...
In statistics, the logistic model (or logit model) is a statistical model that models the log-odds of an event as a linear combination of one or more independent variables. In regression analysis, logistic regression [1] (or logit regression) estimates the parameters of a logistic model (the coefficients in the linear or non linear combinations).