Predicting the Probability of Correct Classification ; CU-CS-974-04

Probabilistic Random Forests: Predicting Data Point Specific Misclassification Probabilities ; CU-CS-954-03

Recently proposed classification algorithms give estimates or worst-case bounds for the probability of misclassification [Lanckriet et al., 2002][L. Breiman, 2001]. These accuracy estimates are for all future predictions, even though some predictions are more likely to be correct than others. This paper introduces Probabilistic Random Forests (PRF), which is based on two existing algorithms, Mi...

Case Study: Debugging a Discovered Specification for java.util.ArrayList by Using Algebraic Interpretation ; CU-CS-970-04

Resources classification using fractal modelling in Eastern Kahang Cu-Mo porphyry deposit, Central Iran

Resources/reserves classification is crucial for block model creation utilised in mine planning and feasibility study. Selection of estimation methods is an essential part of mineral exploration and mining activities. In other word, resources classification is an issue for mining companies, investors, financial institutions and authorities, but it remains subject to some confusion. The aim of t...

Predicting The Type of Malaria Using Classification and Regression Decision Trees

Predicting The Type of Malaria Using Classification and Regression Decision Trees Maryam Ashoori1 *, Fatemeh Hamzavi2 1School of Technical and Engineering, Higher Educational Complex of Saravan, Saravan, Iran 2School of Agriculture, Higher Educational Complex of Saravan, Saravan, Iran Abstract Background: Malaria is an infectious disease infecting 200 - 300 million people annually. Environme...

Predicting the Probability of Correct Classification

We propose a formulation for binary classification, called the Probabilistic CDF algorithm, that both makes a classification prediction, and estimates the probability that the classification is correct. Our model space consists of the widely used basis function models (which includes support vector machines and other kernel classifiers). Our formulation is based on using existing algorithms (su...