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- LSTM Description: LSTM, which stands for 'Long Short-Term Memory', is a type of recurrent neural network (RNN) architecture designed to learn and(...) Read more
- Lagged Variables Description: Lagged variables are those that represent the value of a variable at a previous point in time. In the context of predictive(...) Read more
- Likelihood Function Description: The likelihood function is a fundamental concept in statistics and probability theory that measures the plausibility of a model(...) Read more
- Logit Model Description: The Logit model is a type of regression model used to analyze binary outcome variables, meaning those that can only take two(...) Read more
- Logistic Loss Description: Logistic loss is a loss function used in binary classification problems, measuring the discrepancy between model predictions and(...) Read more
- Laplacian Smoothing Description: Laplacian smoothing is a technique used to smooth data in a way that preserves the overall structure. This technique is based on(...) Read more
- Likelihood Ratio Description: The likelihood ratio is a fundamental statistic in the realm of predictive analysis and statistics, used to compare the goodness of(...) Read more
- Local Regression Description: Local regression is a statistical analysis method used to fit multiple regressions in localized subsets of data. Unlike global(...) Read more
- Latent Class Analysis Description: Latent Class Analysis (LCA) is a statistical method that identifies unobserved subgroups within a population based on observational(...) Read more
- Labeling Function Description: The labeling function is an essential component in the field of machine learning and artificial intelligence, responsible for(...) Read more
- Linguistic Variable Description: A linguistic variable is a type of variable characterized by having values that are words or phrases instead of numbers. These(...) Read more
- Logistic Growth Model Description: The Logistic Growth Model is a mathematical approach that describes how a population grows in a limited environment, taking into(...) Read more
- Laplacian Filter Description: The Laplacian filter is an image processing technique used to enhance edges in images. It is based on the Laplacian operator, which(...) Read more
- Linear Programming Description: Linear programming is a mathematical method used to optimize an outcome given a set of linear constraints. This approach is based(...) Read more
- Laplacian Matrix Description: The Laplacian Matrix is a matrix representation of a graph that describes the connectivity of the graph's vertices. It is defined(...) Read more
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