Usually, the higher the Lift, the better the model.Ĭumulative gain curve : The gain curve represents the sensitivity, or recall, as a function of the percentage of the total population. A Lift of 1 means that there is no gain over an algorithm that makes random predictions. Lift is the ratio between the proportion of true positives and the proportion of positive predictions. Lift curve : The Lift curve is the curve that represents the Lift value as a function of the percentage of the population. The terms used come from signal detection theory. The ROC curve ( Receiver Operating Characteristics ) displays the performance of a model and enables a comparison to be made with other models. In the case of a qualitative depending variable with only two categories, the user will be able to compare the performances of both methods by using ROC curves, Lift curves, or Cumulative gain curves. In the case of a Discriminant analysis or logistic regression, only qualitative dependent variables can be used. XLSTAT uses the CHAID, exhaustive CHAID, QUEST and C&RT (Classification and Regression Trees) algorithms.Ĭlassification and regression trees apply to quantitative and qualitative dependent variables. Use regression tree to build an explanatory and predicting model for a dependent quantitative variable based on explanatory quantitative and qualitative variables.Īlgorithms for classification and regression trees in XLSTAT.Use classification trees to explain and predict the belonging of objects (observations, individuals) to a class, on the basis of explanatory quantitative and qualitative variables.We distinguish the following two cases where these modeling techniques should be used: Two of the strengths of this method are on the one hand the simple graphical representation by trees, and on the other hand the compact format of the natural language rules.
What are classification and regression treesĬlassification and regression trees are methods that deliver models that meet both explanatory and predictive goals.
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