zhao.algorithmMagic.algorithm.classificationAlgorithm.SampleClassification Maven / Gradle / Ivy
package zhao.algorithmMagic.algorithm.classificationAlgorithm;
import zhao.algorithmMagic.operands.matrix.DoubleMatrix;
import zhao.algorithmMagic.operands.matrix.IntegerMatrix;
import zhao.algorithmMagic.operands.vector.DoubleVector;
import zhao.algorithmMagic.operands.vector.IntegerVector;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.Map;
/**
* 样本分类计算组件的统一抽象接口，其中包含通过类别的标准来确定所有待分类的特征类别。
*
* The unified abstract interface of the sample classification calculation component, which includes the determination of all feature categories to be classified through the category criteria.
*
* @author zhao
*/
public interface SampleClassification {
/**
* 计算一个矩阵中所有行或列的数据类别，并将计算之后的数据类别样本返回出去。
*
* Calculate the data categories of all rows or columns in a matrix, and return the calculated data category samples.
*
* @param data 需要被计算的特征数据组成的矩阵。
*
* Matrix composed of characteristic data to be calculated.
* @param categorySample 本次类别计算的类别样本，用于区别各类数据样本，其中的key就是类别，value就是数据特征向量序列，例如：
* {"person", [1,2,3,4,5]},{"insect", [3, 2, 3, 4, 5]}
*
* The category sample of this category calculation is used to distinguish various data samples. The key is the category, and the value is the data feature vector sequence, for example:
* {"person", [1,2,3,4,5]},{"insect", [3, 2, 3, 4, 5]}
* @return 按照指定类别进行分类的数据，例如：
* {"person", ["tom的特征向量", "zhao的特征向量"], "insect", ["蜘蛛的特征向量", "蜗牛的特征向量"]}
*
* Data classified according to the specified category, for example:
* {"person", ["Tom's feature vector", "Zhao's feature vector"], "insert", ["spider's feature vector", "snail's feature vector"]}
*/
HashMap> classification(double[][] data, Map categorySample);
/**
* 计算一个矩阵中所有行或列的数据类别，并将计算之后的数据类别样本返回出去。
*
* Calculate the data categories of all rows or columns in a matrix, and return the calculated data category samples.
*
* @param data 需要被计算的特征数据组成的矩阵。
*
* Matrix composed of characteristic data to be calculated.
* @param categorySample 本次类别计算的类别样本，用于区别各类数据样本，其中的key就是类别，value就是数据特征向量序列，例如：
* {"person", [1,2,3,4,5]},{"insect", [3, 2, 3, 4, 5]}
*
* The category sample of this category calculation is used to distinguish various data samples. The key is the category, and the value is the data feature vector sequence, for example:
* {"person", [1,2,3,4,5]},{"insect", [3, 2, 3, 4, 5]}
* @return 按照指定类别进行分类的数据，例如：
* {"person", ["tom的特征向量", "zhao的特征向量"], "insect", ["蜘蛛的特征向量", "蜗牛的特征向量"]}
*
* Data classified according to the specified category, for example:
* {"person", ["Tom's feature vector", "Zhao's feature vector"], "insert", ["spider's feature vector", "snail's feature vector"]}
*/
HashMap> classification(int[][] data, Map categorySample);
/**
* 计算一个矩阵中所有行或列的数据类别，并将计算之后的数据类别样本返回出去。
*
* Calculate the data categories of all rows or columns in a matrix, and return the calculated data category samples.
*
* @param data 需要被计算的特征数据组成的矩阵。
*
* Matrix composed of characteristic data to be calculated.
* @param categorySample 本次类别计算的类别样本，用于区别各类数据样本，其中的key就是类别，value就是数据特征向量序列，例如：
* {"person", [1,2,3,4,5]},{"insect", [3, 2, 3, 4, 5]}
*
* The category sample of this category calculation is used to distinguish various data samples. The key is the category, and the value is the data feature vector sequence, for example:
* {"person", [1,2,3,4,5]},{"insect", [3, 2, 3, 4, 5]}
* @return 按照指定类别进行分类的数据，例如：
* {"person", ["tom的特征向量", "zhao的特征向量"], "insect", ["蜘蛛的特征向量", "蜗牛的特征向量"]}
*
* Data classified according to the specified category, for example:
* {"person", ["Tom's feature vector", "Zhao's feature vector"], "insert", ["spider's feature vector", "snail's feature vector"]}
*/
HashMap> classification(DoubleMatrix data, Map categorySample);
/**
* 计算一个矩阵中所有行或列的数据类别，并将计算之后的数据类别样本返回出去。
*
* Calculate the data categories of all rows or columns in a matrix, and return the calculated data category samples.
*
* @param data 需要被计算的特征数据组成的矩阵。
*
* Matrix composed of characteristic data to be calculated.
* @param categorySample 本次类别计算的类别样本，用于区别各类数据样本，其中的key就是类别，value就是数据特征向量序列，例如：
* {"person", [1,2,3,4,5]},{"insect", [3, 2, 3, 4, 5]}
*
* The category sample of this category calculation is used to distinguish various data samples. The key is the category, and the value is the data feature vector sequence, for example:
* {"person", [1,2,3,4,5]},{"insect", [3, 2, 3, 4, 5]}
* @return 按照指定类别进行分类的数据，例如：
* {"person", ["tom的特征向量", "zhao的特征向量"], "insect", ["蜘蛛的特征向量", "蜗牛的特征向量"]}
*
* Data classified according to the specified category, for example:
* {"person", ["Tom's feature vector", "Zhao's feature vector"], "insert", ["spider's feature vector", "snail's feature vector"]}
*/
HashMap> classification(IntegerMatrix data, Map categorySample);
}