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java - 使用arff文件存储数据

转载 作者:行者123 更新时间:2023-12-02 05:01:29 28 4
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我正在使用此示例为我的 weka projext enter link description here 创建 .arff 文件.

double[][] data = {{4058.0, 4059.0, 4060.0, 214.0, 1710.0, 2452.0, 2473.0, 2474.0, 2475.0, 2476.0, 2477.0, 2478.0, 2688.0, 2905.0, 2906.0, 2907.0, 2908.0, 2909.0, 2950.0, 2969.0, 2970.0, 3202.0, 3342.0, 3900.0, 4007.0, 4052.0, 4058.0, 4059.0, 4060.0}, 
{19.0, 20.0, 21.0, 31.0, 103.0, 136.0, 141.0, 142.0, 143.0, 144.0, 145.0, 146.0, 212.0, 243.0, 244.0, 245.0, 246.0, 247.0, 261.0, 270.0, 271.0, 294.0, 302.0, 340.0, 343.0, 354.0, 356.0, 357.0, 358.0}};

int numInstances = data[0].length;

FastVector atts = new FastVector();
ArrayList<Instance> instances = new ArrayList<Instance>();
for (int dim = 0; dim < 2; dim++) {
// Create new attribute / dimension
Attribute current = new Attribute("Attribute" + dim, dim);
// Create an instance for each data object


if (dim == 0) {
for (int obj = 0; obj < numInstances; obj++) {
instances.add(new SparseInstance(0));

}
}

// Fill the value of dimension "dim" into each object
for (int obj = 0; obj < numInstances; obj++) {
instances.get(obj).setValue(current, data[dim][obj]);
System.out.println(instances.get(obj));
}

// Add attribute to total attributes
atts.addElement(current);

}

// Create new dataset
Instances newDataset = new Instances("Dataset", atts, instances.size());

// Fill in data objects
for (Instance inst : instances) {
newDataset.add(inst);
}

BufferedWriter writer = new BufferedWriter(new FileWriter("test.arff"));
writer.write(newDataset.toString());
writer.flush();
writer.close();
}

我注意到结果格式将行元素放入 vector 在 .arff 文件的列中。我想将整行放在 .arff 文件的第一行中。我怎样才能这样做?对于我的情况,二维 vector 的最后一列表示行数据的标签。

我的 arff 文件的预期结果:

4058.0, 4059.0, 4060.0, 214.0, 1710.0, 2452.0, 2473.0, 2474.0, 2475.0, 2476.0, 2477.0, 2478.0, 2688.0, 2905.0, 2906.0, 2907.0, 2908.0, 2909.0, 2950.0, 2969.0, 2970.0, 3202.0, 3342.0, 3900.0, 4007.0, 4052.0, 4058.0, 4059.0, 4060.0, 1 // for example the first row
19.0, 20.0, 21.0, 31.0, 103.0, 136.0, 141.0, 142.0, 143.0, 144.0, 145.0, 146.0, 212.0,
243.0, 244.0, 245.0, 246.0, 247.0, 261.0, 270.0, 271.0, 294.0, 302.0, 340.0, 343.0,
354.0, 356.0, 357.0, 358.0, 0 // the second row.

最佳答案

示例中的代码将表中的每一列视为一个实例(因此有 29 个实例,每个实例都有两个属性)。听起来您想将每一行视为一个实例(给出两个实例,每个实例有 29 个属性):

double[][] data = {
{4058.0, 4059.0, ... }, /* first instance */
{19.0, 20.0, ... } /* second instance */
};

int numAtts = data[0].length;
FastVector atts = new FastVector(numAtts);
for (int att = 0; att < numAtts; att++)
{
atts.addElement(new Attribute("Attribute" + att, att));
}

int numInstances = data.length;
Instances dataset = new Instances("Dataset", atts, numInstances);
for (int inst = 0; inst < numInstances; inst++)
{
dataset.add(new Instance(1.0, data[inst]));
}

BufferedWriter writer = new BufferedWriter(new FileWriter("test.arff"));
writer.write(dataset.toString());
writer.flush();
writer.close();

我将 SparseInstance 替换为 Instance,因为几乎所有属性值都不为零。请注意,在 Weka 3.7 中,Instance 已成为一个接口(interface),应使用 DenseInstance 来代替。此外,FastVector 已被弃用,取而代之的是 Java 的 ArrayList

关于java - 使用arff文件存储数据,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/21723013/

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