Highlighting Potential Biases

Dec 1, 2023 ... ... categorical data into a format that can be understood by the AI algorithms. ... One of the primary concerns in AI is 'informational privacy ... Jul 28, 2020 ... Informational discontinuity can have far reaching consequences like ... The categorical variables were analyzed using Chi-square test. Dec 10, 2020 ... It is commonly used in the construction of decision trees from a training dataset, by evaluating the information gain for each variable, and ... More specifically, categorical data may derive from observations made of qualitative data that are summarised as counts or cross tabulations, or from ... EXST7036 Categorical Data Analysis; EXST7037 Multivariate Statistics; EXST7038 Statistical Methods for Spatial Data; EXST7142 Statistical DAta Mining; EXST7151 ... Jul 3, 2019 ... A categorical designation that refers to unclassified information that ... information; data or statements; trade secrets; product research and. From the fMRI data, we generated a whole-brain activation map for each concept, reflecting the unique spatial pattern of neural activity for that concept (Fig. Informational Text. The Bachelor of Science in Computing & Information ... STA4504 (GM) Categorical Data Analysis (3 credits). Major Electives (9 ... Nov 21, 2024 ... ... information into data that's pertinent to the research question. Categorical data is qualitative because it lacks a fixed metric, making it ... Data Analytics in R; Applied Categorical Data Analysis; Applied Time Series Analysis; Special Topics in Data Analytics; Cybersecurity Forensics. View Catalog ...