density of training data
1Density functional theory — Electronic structure methods Tight binding Nearly free electron model Hartree–Fock method Modern valence bond Generalized valence bond Møller–Plesset perturbation theory …
2Modular data center — A 40 foot Portable Modular Data Center …
3Motorcycle training — Army National Guard motorcycle riders hone their skills during the Army Guard hosted Motorcycle Safety Foundation Sport bike Rider Certification Course. January 30, 2009 at Fort Rucker, Alabama. Motorcycle training teaches motorcycle riders the… …
4Silt Density Index — The silt density index is a measure for the fouling capacity of water in reverse osmosis systems. SDI values below 5 result in low fouling rates. The Silt Density Index (SDI) test is used to determine the fouling potential of waterfeeding a… …
5Cross-validation (statistics) — Cross validation, sometimes called rotation estimation,[1][2][3] is a technique for assessing how the results of a statistical analysis will generalize to an independent data set. It is mainly used in settings where the goal is prediction, and… …
6Vector quantization — is a classical quantization technique from signal processing which allows the modeling of probability density functions by the distribution of prototype vectors. It was originally used for data compression. It works by dividing a large set of… …
7k-nearest neighbor algorithm — KNN redirects here. For other uses, see KNN (disambiguation). In pattern recognition, the k nearest neighbor algorithm (k NN) is a method for classifying objects based on closest training examples in the feature space. k NN is a type of instance… …
8Multispectral pattern recognition — Multispectral remote sensing is the collection and analysis of reflected, emitted, or back scattered energy from an object or an area of interest in multiple bands of regions of the electromagnetic spectrum (Jensen, 2005). Subcategories of… …
9Supervised learning — is a machine learning technique for learning a function from training data. The training data consist of pairs of input objects (typically vectors), and desired outputs. The output of the functioncan be a continuous value (called regression), or… …
10K-nearest neighbor algorithm — In pattern recognition, the k nearest neighbor algorithm ( k NN) is a method for classifying objects based on closest training examples in the feature space. k NN is a type of instance based learning, or lazy learning where the function is only… …
