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An embedded case study is a case study containing more than one sub-unit of analysis (Yin, 2003). Similar to a case study, an embedded case study methodology provides a means of integrating quantitative and qualitative methods into a single research study (Scholz & Tietje, 2002; Yin 2003). However, the identification of sub-units allows for a ...
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 ...
Rather than repeating the algorithm m times, implement it exhaustively (i.e. n times, once for each instance) for relatively small n (up to one thousand). Furthermore, rather than finding the single nearest hit and single nearest miss, which may cause redundant and noisy attributes to affect the selection of the nearest neighbors, ReliefF searches for k nearest hits and misses and averages ...
In statistics, qualitative comparative analysis (QCA) is a data analysis based on set theory to examine the relationship of conditions to outcome. QCA describes the relationship in terms of necessary conditions and sufficient conditions . [ 1 ]
Embedded methods are a catch-all group of techniques which perform feature selection as part of the model construction process. The exemplar of this approach is the LASSO method for constructing a linear model, which penalizes the regression coefficients with an L1 penalty, shrinking many of them to zero.
Common research designs and data collection methods include: 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 ...
Computer-assisted (or aided) qualitative data analysis software (CAQDAS) offers tools that assist with qualitative research such as transcription analysis, coding and text interpretation, recursive abstraction, content analysis, discourse analysis, [1] grounded theory methodology, etc.
Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning.In this formalism, a classification or regression decision tree is used as a predictive model to draw conclusions about a set of observations.