Learner, Practitioner & Teacher
Need: In any research/ model, identifying the key interactions (combination of different variable &levels) which will explain the more variance of the dependent variable is really important. But identifying these interactions is really tedious task due to the number of
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Need: In any research, before it starts, we need to review the existing scientific literature as well as available past research around that topic (i.e., existing publications, articles around that topic). But it is really tedious task where we need
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It’s clear that the pandemic has accelerated the digitization of the healthcare industry. According to the HIMSS Future of Healthcare Report, 80% of healthcare providers plan to increase investment in technology and digital solutions over the next five years. We
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Need: In any classification analysis, if you want to measure the overall agreement between predicted and observed levels this measure will be very useful. Unlike Precision and Recall, and F1 score , Kappa co efficient considers perfect agreement between both
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Need: Whenever you want to combine & analyze several trials and also you want to estimate the summary treatment effect based on various trails or you want to obtain a finding that is beyond (single) effects found in different studies,
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Need: When conducting multiple analyses on the same dependent variable, the chance of committing a Type I error increases, thus increasing the likelihood of coming about a significant result by pure chance. To correct for this, or protect from Type
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Need The number of input variables or features for a dataset is referred to as its dimensionality. Dimensionality reduction refers to techniques that reduce the number of input variables in a dataset. More input features often make a predictive modeling
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Need Cluster analysis is widely adopted by various applications like image processing, neuroscience, economics, network communication, medicine, recommendation systems, customer segmentation, to name a few. Additionally, clustering can be considered the initial step when dealing with a new dataset to
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