Example data and definition files are provided in the examples\datafiles directory. These files may be used by any bean. Sometimes companion data is provided for testing with a suffix of Test.

The following sample data sources are provided:

Animal
  This file contains descriptions of seven different animals and is used for supervised learning techniques. The file with the Test suffix can be used to verify training. The file with the suffix Test2 contains an additional record designed to illustrate the need to provide all possible values during training and provide the opportunity for the user to create a custom filter to put more credance in the weight field.
  Uses: AbleNeuralClassifierAgent, AbleDecisionTree.
  Statistics: 7 records; inputs: 5 categorical, 1 discrete, 1 continuous; outputs: 1 categorical.
BondRating
  This file contains data about various bond issues and can be used to rank the most promising issues using a fuzzy ruleset.
  Uses: AbleFuzzyRuleSet, AbleDecisionTree, AbleSelfOrganizingFeatureMap.
  Statistics: 37 records; inputs: 4 continuous; outputs: 0.
coc1
  This file is a binary dataset used for supervised learning techniques.
  Uses: AbleNaiveBayes.
  Statistics: 1600 records; inputs: 59 discrete; outputs: 1 discrete.
CoinIdentifier
  This file contains descriptions of five different United States coins and is used for supervised learning techniques.
  Uses: AbleNeuralClassifierAgent, AbleDecisionTree.
  Statistics: 5 records; inputs: 6 categorical; outputs: 1 categorical.
ColorScore
  Each record in this file contains two colors, a numeric indicator, and the resultant score. This example is useful for supervised learning beans for classification.
  Uses: AbleDecisionTree.
  Statistics: 15 records; inputs: 2 categorical, 1 continuous; outputs: 1 categorical.
CreditScore
  This file contains credit and financial history for individuals and is used to calculate credit limits. This example is useful for supervised learning beans for classification. If modified for unsupervised learning, it could be used to categorize an individual's credit worthiness by assigning them to a cluster with similar characteristics.
  Uses: AbleNeuralClassificationAgent, AbleNeuralPredictionAgent.
  Statistics: 148 records; inputs: 2 categorical, 3 continuous, 1 discrete; outputs: 1 categorical.
DiscountCustomer
  Each record in this file contains a customer transaction request consisting of the customer id and name, item to purchase, and list price. This data is used by the DiscountAgent example for CommonRules.
  Uses: AbleCommonRules.
  Statistics: 2 records; inputs: 3 categorical, 2 continuous, 1 discrete; outputs: 0.
MarketAnalysis
  This file contains past records of purchases by customers and some information about that customer. It is used to cluseter similar customers into groups for target marketing. It is used for unsupervised learning.
  Uses: AbleNeuralClusteringAgent, AbleSelfOrganizingFeatureMap.
  Statistics: 300 records; inputs: 1 categorical, 5 continuous; outputs: 0.
Medical
  The records in this file represent patient symptoms. It is used to diagnose medical conditions using a fuzzy ruleset.
  Uses: AbleFuzzyRuleSet.
  Statistics: 12 records; inputs: 9 categorical, 1 continuous; outputs: 0.
Mortgage
  This file contains information describing mortgage requests and their dispositions. It is used for supervised learning techniques. The file with the Test suffix can be used to verify training.
  Uses: AbleNeuralClassifierAgent, AbleFuzzyRuleSet.
  Statistics: 30 records; inputs: 1 categorical, 1 discrete, 9 continuous, 1 ignore; outputs: 6 categorical.
PolicyTest1
  This file contains high level descriptors of system load and corresponding status for use in setting service level policies. The agent using it is an example of multiple rule sets.
  Uses: AbleRuleSet.
  Statistics: 12 records; inputs: 2 categorical; outputs: 0.
SalesForecast
  Each record represents a store's sales on a particular day. The objective is to forecast the change in sales for the following day.
  Uses: AbleBackPropagation (recurrent), AbleRadialBasisFunctionNet.
  Statistics: 365 records; inputs: 2 continuous, 2 discrete; outputs: 1 continuous.
SystemManagement
  Each record in this file contains a snapshot of a system's performance values at a point in time. This example is useful for supervised learning beans for classification. The output class is the system utilization level - one of idle, underused, normal, overused, or danger.
  Uses: AbleBackPropagation.
  Statistics: 15 records; inputs: 4 categorical, 2 discrete, 13 continuous; outputs: 1 categorical.
Tdwalk
  Each record in this file is one step in a sequence. The boolean value true indicates the object location. When the object reaches the leftmost or rightmost position, the sequence ends. Because of the unique flags that indicate the start, middle, and end of the sequence, this data is useful only for temporal difference learning.
  Uses: AbleTemporalDifferenceLearning.
  Statistics: 2008 records; inputs: 6 continuous; outputs: 1 continuous.
Trout
  Each record contains the attributes describing the appearance of one of nine Wyoming game fish. This example is used by supervised learning beans such as neural classification and decision tree. Ignore the fish type field if to be used in unsupervised learning. The first 100 records can be used for training, and the last 25 for testing. Within each of those groups, the records are sorted by fish type so some algorithms may wish to use the randomize feature of the AbleImport bean.
  Uses: AbleNeuralClassifierAgent (with randomize), AbleNeuralPredictionAgent, AbleDecisionTree, AbleFuzzyRuleSet.
  Statistics: 125 records; inputs: 5 categorical, 2 continuous, 1 discrete; outputs: 1 categorical.
Vehicle
  This file contains data describing various vehicles. It can be used to for either forward or backward chaining in boolean rulesets.
  Uses: AbleRuleSet.
  Statistics: 7 records; inputs: 3 categorical, 2 discrete; outputs: 0.
xor
  Each record in this file contains two binary inputs and the result of the exclusive OR operation applied to those inputs. This example is useful for supervised learning beans for classification.
  Uses: AbleNeuralPredictionAgent.
  Statistics: 4 records; inputs: 2 continuous; outputs: 1 continuous.