Here is a mex implementation of a Parzen classifier
Ruby interface to the CRM114 Controllable Regex Mutilator, an advanced and fast text classifier that uses sparse binary polynomial matching with a Bayesian Chain Rule evaluator and a hidden Markov model to categorize data with up to a 99.87%...
Vorras Classifier is Unix compatible. Vorras Classifier is a server-side email anti-spam tool that relies on machine learning technology to distinguish between spam and legitimate email messages. Decisions on incoming email are based on a database...
Directory Classifier lets you view a customizable listing of the contents for any directory on your computer. You can easily save the folder listing as TXT or PDF file. The listing can be imported into most popular spreadsheets and database...
SC - Sparse Classifier FSC - Fast Sparse Classifier GSC - Group Sparse Classifier FGSC - Fast Group Sparse Classifier NSC - Nearest Subspace Classifier
Requires SPGL1 - http://www.cs.ubc.ca/labs/scl/spgl1/
SVMs are a bit tricky. In this case, we show a linear SVM and illustrate its behaviour on some 2D data. This should be great for getting to grips with maximising geometric margins, support vectors, and the optimisation involved in computing an...
It is known that there is no sufficient Matlab program about neuro-fuzzy classifiers. Generally, ANFIS is used as classifier. ANFIS is a function approximator program. But, the usage of ANFIS for classifications is unfavorable. For example, there...
A fast Gentle Adaboost classifier with two different weak-learners: i) decision stump and ii) perceptron. Multiclass is performed with the one-against-all strategy.
Usage ------
model = gentleboost_model(X , y , [T] ,...
Fuzzy k-nearest neighbors classifier that can work with training samples whose label info is fuzzified. The prototype is as follows.
[y,predict_class] = f_knn(tr,tr_memberships,te,k)
tr: training samples tr_memberships:...
In pattern recognition, and in particular multiple classifier systems, a common problem is to calculate competence of a classifier for a given object. Methods for calculating the competence currently developed are based only on crisp decision of...
This little package contains a Parzen Neural Network classifier that can classify data between N classes in D dimensions. The classifier is really fast and simple to learn. The good classification performance can be obtained for a certain class of...
This classifier is based on the idea that first we create ideal vectors from each class. In this implementation mean vectors are used. Then, it uses similarity measure to calculate similarities between samples and idealvectors and class of the...
"Pegasos-Primal Estimated sub-Gradient SOlver for SVM" is a primal optimization problem solver in Support Vector Machine classification algorithm. See the paper for further reference.
This code provides a two simple examples of naive Bayes classifier. In the first example the input are a bunch of positive and negative numbers and their corresponding classes i.e. posi or negi and is tested with random numbers.
...
Kernel version of the sparse representations classifier implemented with CVX #The kernel sparse representations classifier implemented here is # based on the paper 1)Robust Face Recgnition via Sparse Representation John Wright,...
Genetic Programming Classifier is a distributed evolutionary data classification program. It uses the ensemble method implemented under a parallel co-evolutionary Genetic Programming technique.
dbacl is a general purpose digramic Bayesian text classifier. It can learn text documents you provide, and then compare new input with the learned categories. It can be used for spam filtering, or within your own shell scripts. Sometimes it plays che
This is a classifier that determines the type of a word in a human knowledge context (dates, money, percentage, proper names, etc.)
SFAM is an incremental neural network classifier. It is a simple and fast version of Fuzzy ARTMAP (FAM). Both FAM and SFAM produce the same output given the same input.
References: [1] Kasuba, T. (1993). "Simplified fuzzy...
This color reduction software is based on a new neural network classifier (SGONG). The SGONG network classifier is suitable for color quantization applications, since each image pixel is considered as multidimensional vector, depending on the... |