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java.lang.Objectprea.recommender.CustomRecommender
public class CustomRecommender
This is a skeleton class for user-defined custom recommenders. You may copy this class if you want to implement more than one class. Please look at the "COMMENT FOR AUTHORS" in each method carefully before coding your algorithm.
Field Summary | |
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int |
itemCount
The number of items. |
double |
maxValue
Maximum value of rating, existing in the dataset. |
double |
minValue
Minimum value of rating, existing in the dataset. |
SparseMatrix |
rateMatrix
Rating matrix for each user (row) and item (column) |
int |
userCount
The number of users. |
Constructor Summary | |
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CustomRecommender(int uc,
int ic,
double max,
double min)
Construct a customized recommender model with the given data. |
Method Summary | |
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void |
buildModel(SparseMatrix rm)
Build a model with the given data and algorithm. |
EvaluationMetrics |
evaluate(SparseMatrix testMatrix)
Evaluate the designated algorithm with the given test data. |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
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public SparseMatrix rateMatrix
public int userCount
public int itemCount
public double maxValue
public double minValue
Constructor Detail |
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public CustomRecommender(int uc, int ic, double max, double min)
uc
- The number of users in the dataset.ic
- The number of items in the dataset.max
- The maximum rating value in the dataset.min
- The minimum rating value in the dataset.Method Detail |
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public void buildModel(SparseMatrix rm)
buildModel
in interface Recommender
rm
- The rating matrix with train data.public EvaluationMetrics evaluate(SparseMatrix testMatrix)
evaluate
in interface Recommender
testMatrix
- The rating matrix with test data.
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