<prompt> Bolela le ho hlalosa marena a mararo a lihlopha.nan  <response>: Instruction in English: Name and define three kings of classification. . Response in English: Classification is a technique used in machine learning and data analysis to categorize data into distinct groups based on specific characteristics. There are several types of classification techniques, including:1. Logistic Regression: This is a statistical method of classification that uses a logistic function to model a binary dependent variable. In other words, it is used to predict the probability of an event occurring based on the presence of certain predictors or independent variables.2. Decision Tree: A decision tree is a tree-like graphical model used for classification, where internal nodes represent tests on an attribute or feature, branches represent the outcome of these tests, and leaf nodes represent class labels. The goal of a decision tree is to split the data into subsets based on different values of the attributes, then make a prediction based on the majority class in each subset.3. K-Nearest Neighbors KNN: KNN is a non-parametric method of classification that involves finding the K nearest neighbors to a query sample, then predicting the class of that sample based on the majority class of its neighbors. The distance between samples is calculated using metrics such as Euclidean distance or Manhattan distance, and the value of K is typically chosen via cross-validation. . Response in Sesotho: Classification ke mokhoa o sebelisoang thutong ea mochini le tlhahlobo ea data ho arola lintlha ka lihlopha tse ikhethileng ho ipapisitse le litšobotsi tse itseng. Ho na le mefuta e maloa ea mekhoa ea ho arola, e kenyeletsang: 1. Logistic Regression: Ena ke mokhoa oa lipalo-palo oa ho arola o sebelisang mosebetsi oa ho etsa mohlala oa phetoho e itšetlehileng ka binary. Ka mantsoe a mang, e sebelisoa ho bolela esale pele monyetla oa hore ketsahalo e etsahale ho latela boteng ba li-predictors tse itseng kapa mefuta e ikemetseng. 2. Sefate sa Qeto: Sefate sa liqeto ke mohlala oa litšoantšo o kang oa sefate o sebelisetsoang ho arola, moo li-node tsa ka hare li emelang liteko ka tšobotsi kapa tšobotsi, makala a emela sephetho sa liteko tsena, me li-node tsa makhasi li emela li-label tsa lihlopha. Sepheo sa sefate sa liqeto ke ho arola lintlha ka likaroloana tse thehiloeng ho boleng bo fapaneng ba litšoaneleho, ebe u etsa ponelopele ho latela sehlopha sa bongata sehlopheng ka seng. 3. Baahelani ba K-Nearest KNN: KNN ke mokhoa o seng oa parametric oa ho arola o kenyelletsang ho fumana K baahelani ba haufi le sampole ea potso, ebe o bolela esale pele sehlopha sa sampole eo ho ipapisitsoe le bongata ba baahelani ba eona. Sebaka se pakeng tsa lisampole se baloa ho sebelisoa metrics joalo ka sebaka sa Euclidean kapa sebaka sa Manhattan, me boleng ba K hangata bo khethoa ka netefatso e fapaneng. 