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<script> | |
export let name; | |
let input = { | |
row : { start: 0, end: 0 }, | |
column : { start: 1, end: 100 } | |
} | |
let id = 0 | |
let columnCount = 480 | |
let classPeriods = [] | |
function addClassPeriod() { |
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//..FileHandler Verticle | |
router.post("/fileUpload").handler(BodyHandler.create().setMergeFormAttributes(true)).handler { | |
println(it.fileUploads().size) | |
it.fileUploads().forEach({ | |
println(it.fileName()) | |
}) | |
it.response().end( |
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name | value | |
---|---|---|
Locke | 4 | |
Reyes | 8 | |
Ford | 15 | |
Jarrah | 16 | |
Shephard | 23 | |
Kwon | 42 |
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import java.util.Random; | |
import org.deeplearning4j.datasets.iterator.DataSetIterator; | |
import org.deeplearning4j.datasets.iterator.impl.IrisDataSetIterator; | |
import org.nd4j.linalg.api.ndarray.INDArray; | |
import org.nd4j.linalg.api.ops.impl.accum.distances.EuclideanDistance; | |
import org.nd4j.linalg.dataset.DataSet; | |
import org.nd4j.linalg.dataset.SplitTestAndTrain; | |
import org.nd4j.linalg.factory.Nd4j; | |
import org.slf4j.Logger; |
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import org.nd4j.linalg.api.ndarray.INDArray; | |
import org.nd4j.linalg.api.ops.BaseAccumulation; | |
import org.nd4j.linalg.api.ops.impl.accum.distances.EuclideanDistance; | |
import org.nd4j.linalg.dataset.api.DataSet; | |
import org.nd4j.linalg.factory.Nd4j; | |
/** | |
* Requires RC1<br/> | |
* This is a sample implementation of K-Nearest Neighbor. KNN doesn't create a latent/hidden model, nor does it train. It simply uses it's dataset as a look up table. | |
* Then grabs the closest k data point/records. From there it is able to look at the labels for the K nearest neighbors and make a decision on what label to predict the incoming |
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<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" | |
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"> | |
<modelVersion>4.0.0</modelVersion> | |
<groupId>com.mygroup</groupId> | |
<artifactId>deeplearning-bt</artifactId> | |
<version>0.0.1-SNAPSHOT</version> | |
<packaging>jar</packaging> | |
<name>deeplearning-bt</name> |