Clojure Machine Learning Libraries:

CJ-ML : A machine learning library for Clojure built on top of Weka. Supported algorithms include: k-Nearest neighbor, Decision trees,Multilayer perceptrons, Logistic Regression & k Means clusterers

Infer - : Infer is a library for machine learning and statistical inference, designed to be used in real production systems. (Last update was 2010)

Nurokit: General purpose Toolkit for machine learning in Clojure including Neural networks & Visualisation tools (Last update was 2013)

clj-bigml - BigML offers a REST-style service for building, sharing, and evaluating machine learning models. Currently the only model variety supported is CART-style decision trees grown in an anytime, streaming fashion. The trees use standard ML practices such as information gain (or information gain ratio) for classification problems, squared error for regression, and statistical pruning options.

Clojure Enclog: Clojure wrapper for the encog (v3) machine-learning framework. Encog has been around for almost 5 years, and so can be considered fairly mature and optimised. Apart from neural-nets, version 3 introduced SVM and Bayesian classification. With this library, which is a thin wrapper around encog, you can construct and train many types of neural nets in less than 10 lines of pure Clojure code.

FungGP: A genetic programming library for Clojure Genetic programming (GP) is the process of evolving computer programs using a process inspired by biological evolution. In GP, a computer program automatically writes new computer programs (in this case, by generating trees of new Clojure code), and judges them according to their ability to solve a problem or produce correct output. In fungp, like in many GP systems, tree structures representing programs go through processes inspired by biological evolution, such as mutation and reproduction. Their chance of reproduction is decided by their "fitness," which is assigned by a fitness function. For example, a simple problem you might solve with GP is symbolic regression, in which the evolved trees represent mathematical functions mapping one or more inputs to an output, and the fitness function would compile and run the evolved programs on known data to test whether sets of inputs produce correct output.

Synaptic is a Neural Networks library written in Clojure. Synaptic allows to create multilayer feedforward networks and train them using various algorithms such as: perceptron learning rule, backpropagation, L-BFGS (approximation of Newton's method), R-prop, RMSprop , L1 & L2 regularization , convolution / pooling layers

Clojush is a version of the Push programming language for evolutionary computation, and the PushGP genetic programming system, implemented in clojure.