DATA SCIENCE QUESTIONS AND ANSWERS
Jackknife Resampling (Jacknifing) in statistics is a resampling technique especially useful for variance and bias estimation. The jackknife predates other common resampling methods such as the bootstrap. The jackknife estimator of a parameter is found by systematically leaving out each observation from a dataset and calculating the estimate and then finding the average of these calculations. Given a sample of … Read more
Interpolation in the mathematical field of numerical analysis, is a method of constructing new data points within the range of a discrete set of known data points. In engineering and science, one often has a number of data points, obtained by sampling or experimentation, which represent the values of a function for a limited number of values of the independent … Read more
Intercept is the expected mean value of Y when all X=0. If we start with a regression equation with one predictor, X. If X sometimes is equal zero, the intercept is simply the expected mean value of Y at that value. If X never equals zero, then the intercept has no intrinsic meaning. If so, and if X never = … Read more
Information Retrieval (IR) is the action/process of obtaining information resources relevant to an information need from a collection of information resources. Searches can be based on full-text or other content-based indexing. Information retrieval is the science of searching for information in a document, searching for documents themselves, searching for metadata that describes data and for databases such as text, image … Read more
Hopfield Network is a form of recurrent artificial neural network. Hopfield networks are classical models of memory and collective processing in networks of abstract McCulloch-Pitts neurons, but they have not been widely used in signal processing as they usually have small memory capacity (scaling linearly in the number of neurons) and are challenging to train, especially on noisy data. Hopfield … Read more
Homoscedastic ‘in statistics, is a definition of a sequence or a vector of random variables if all random variables in the sequence or vector have the same finite variance. This is also known as the homogeneity of variance. The complementary notion is called heteroscedasticity’. Was the above useful? Please share with others on social media. If you want to look … Read more
Hierarchical Clustering in data mining and statistics (also called hierarchical cluster analysis or HCA) is a method of cluster analysis which seeks to build a hierarchy of clusters. Strategies for hierarchical clustering generally fall into two types: Agglomerative: This is a “bottom up” approach: each observation starts in its own cluster, and pairs of clusters are merged as one moves … Read more
Hidden Markov Model (HMM) is a statistical Markov model in which the system being modeled is assumed to be a Markov process with unobserved (hidden) states. An HMM can be presented as the simplest dynamic Bayesian network. In simpler Markov models (like a Markov chain), the state is directly visible to the observer, and therefore the state transition probabilities are … Read more
Heteroscedasticity refers to the circumstance in which the variability of a variable is unequal across the range of values of a second variable that predicts it. In other words, it refers to data with unequal variability (scatter) across a set of second, predictor variables. Was the above useful? Please share with others on social media. If you want to look … Read more
Hash Table (Hash Map) in computing is a data structure used to implement an associative array, a structure that can map keys to values. A hash table uses a hash function to compute an index into an array of buckets or slots, from which the desired value can be found. Ideally, the hash function will assign each key to a … Read more