👉 Semelparity, also known as "semiparameter" or "semi-parametric", is a concept in machine learning and statistics that refers to a model where the input features are not fully specified but only partially known. This means that there may be some unknown parameters or latent variables that need to be estimated from the data. In semelparity models, the model learns by directly estimating these parameters without explicitly knowing them. This approach is often used in areas such as unsupervised learning,
