Useful tips for everyday
What is the use of entropy and information gain in designing Decision Tree? Well that’s exactly how and why decision trees use entropy and information…
What is the minimum sample size for reliability test? The RCSI sample size handbook: a rough guide Conroy R (2016) This study summarized that sample…
How to evaluate the performance of clustering algorithms? There are various functions with the help of which we can evaluate the performance of clustering algorithms.…
What normalization entails data? Normalization is the process of organizing data in a database. This includes creating tables and establishing relationships between those tables according…
What is the most suitable statistical test for ordinal data? The most suitable statistical tests for ordinal data (e.g., Likert scale) are non-parametric tests, such…
What are the thresholds in ROC curve? What Are ROC Curves? A useful tool when predicting the probability of a binary outcome is the Receiver…
Is a random walk covariance stationary? In general, you should be able to see if your time series has constant mean and variance by plotting…
Which of the following sequencing methods is more suitable for discovering large scale structural variations? Strand-seq Especially, long-read sequencing is powerful to detect structural variants…
What are meta learning strategies? Meta learning is a branch of metacognition concerned with learning about one’s own learning and learning processes. The term comes…
How are forward and backward algorithms used in hidden Markov model? In this Understanding Forward and Backward Algorithm in Hidden Markov Model article we will…