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public interface MLDataSet
An interface designed to abstract classes that store machine learning data. This interface is designed to provide EngineDataSet objects. These can be used to train machine learning methods using both supervised and unsupervised training. Some implementations of this interface are memory based. That is they store the entire contents of the dataset in memory. Other implementations of this interface are not memory based. These implementations read in data as it is needed. This allows very large datasets to be used. Typically the add methods are not supported on non-memory based datasets.
Method Summary | |
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void |
add(MLData data1)
Add a object to the dataset. |
void |
add(MLData inputData,
MLData idealData)
Add a set of input and ideal data to the dataset. |
void |
add(MLDataPair inputData)
Add a an object to the dataset. |
void |
close()
Close this datasource and release any resources obtained by it, including any iterators created. |
MLDataPair |
get(int index)
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int |
getIdealSize()
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int |
getInputSize()
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void |
getRecord(long index,
MLDataPair pair)
Read an individual record, specified by index, in random order. |
long |
getRecordCount()
Determine the total number of records in the set. |
boolean |
isSupervised()
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MLDataSet |
openAdditional()
Opens an additional instance of this dataset. |
int |
size()
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Methods inherited from interface java.lang.Iterable |
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iterator |
Method Detail |
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int getIdealSize()
int getInputSize()
boolean isSupervised()
long getRecordCount()
void getRecord(long index, MLDataPair pair)
index
- The index to read.pair
- The pair that the record will be copied into.MLDataSet openAdditional()
void add(MLData data1)
data1
- The data item to be added.void add(MLData inputData, MLData idealData)
inputData
- Input data.idealData
- Ideal data.void add(MLDataPair inputData)
inputData
- A MLDataPair object that contains both input and ideal data.void close()
int size()
MLDataPair get(int index)
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