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Adding notice and code notice, Daisy system identification: Power Plant
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‎NOTICE

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Apache DynaML
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Copyright 2015 The Apache Software Foundation
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This product includes software developed at
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The Apache Software Foundation (http://www.apache.org/).
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‎data/powerplant.csv

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‎src/main/scala/io/github/mandar2812/dynaml/evaluation/BinaryClassificationMetrics.scala

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/*
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Licensed to the Apache Software Foundation (ASF) under one
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or more contributor license agreements. See the NOTICE file
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distributed with this work for additional information
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regarding copyright ownership. The ASF licenses this file
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to you under the Apache License, Version 2.0 (the
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"License"); you may not use this file except in compliance
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with the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing,
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software distributed under the License is distributed on an
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"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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KIND, either express or implied. See the License for the
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specific language governing permissions and limitations
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under the License.
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* */
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package io.github.mandar2812.dynaml.evaluation
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import breeze.linalg.DenseVector

‎src/main/scala/io/github/mandar2812/dynaml/evaluation/BinaryClassificationMetricsSpark.scala

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/*
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Licensed to the Apache Software Foundation (ASF) under one
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or more contributor license agreements. See the NOTICE file
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distributed with this work for additional information
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regarding copyright ownership. The ASF licenses this file
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to you under the Apache License, Version 2.0 (the
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"License"); you may not use this file except in compliance
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with the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing,
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software distributed under the License is distributed on an
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"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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KIND, either express or implied. See the License for the
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specific language governing permissions and limitations
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under the License.
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* */
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package io.github.mandar2812.dynaml.evaluation
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import breeze.linalg.DenseVector

‎src/main/scala/io/github/mandar2812/dynaml/evaluation/Metrics.scala

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/*
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Licensed to the Apache Software Foundation (ASF) under one
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or more contributor license agreements. See the NOTICE file
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distributed with this work for additional information
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regarding copyright ownership. The ASF licenses this file
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to you under the Apache License, Version 2.0 (the
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"License"); you may not use this file except in compliance
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with the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing,
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software distributed under the License is distributed on an
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"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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KIND, either express or implied. See the License for the
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specific language governing permissions and limitations
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under the License.
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* */
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package io.github.mandar2812.dynaml.evaluation
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import breeze.linalg.DenseVector

‎src/main/scala/io/github/mandar2812/dynaml/evaluation/RegressionMetrics.scala

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/*
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Licensed to the Apache Software Foundation (ASF) under one
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or more contributor license agreements. See the NOTICE file
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distributed with this work for additional information
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regarding copyright ownership. The ASF licenses this file
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to you under the Apache License, Version 2.0 (the
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"License"); you may not use this file except in compliance
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with the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing,
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software distributed under the License is distributed on an
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"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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KIND, either express or implied. See the License for the
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specific language governing permissions and limitations
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under the License.
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* */
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package io.github.mandar2812.dynaml.evaluation
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import breeze.linalg.DenseVector

‎src/main/scala/io/github/mandar2812/dynaml/evaluation/RegressionMetricsSpark.scala

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/*
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Licensed to the Apache Software Foundation (ASF) under one
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or more contributor license agreements. See the NOTICE file
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distributed with this work for additional information
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regarding copyright ownership. The ASF licenses this file
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to you under the Apache License, Version 2.0 (the
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"License"); you may not use this file except in compliance
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with the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing,
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software distributed under the License is distributed on an
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"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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KIND, either express or implied. See the License for the
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specific language governing permissions and limitations
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under the License.
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* */
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package io.github.mandar2812.dynaml.evaluation
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import breeze.linalg.DenseVector

‎src/main/scala/io/github/mandar2812/dynaml/examples/DaisyPowerPlant.scala

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/*
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Licensed to the Apache Software Foundation (ASF) under one
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or more contributor license agreements. See the NOTICE file
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distributed with this work for additional information
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regarding copyright ownership. The ASF licenses this file
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to you under the Apache License, Version 2.0 (the
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"License"); you may not use this file except in compliance
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with the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing,
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software distributed under the License is distributed on an
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"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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KIND, either express or implied. See the License for the
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specific language governing permissions and limitations
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under the License.
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* */
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package io.github.mandar2812.dynaml.examples
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import breeze.linalg.DenseVector
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import com.quantifind.charts.Highcharts._
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import io.github.mandar2812.dynaml.evaluation.RegressionMetrics
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import io.github.mandar2812.dynaml.kernels.LocalSVMKernel
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import io.github.mandar2812.dynaml.models.svm.DLSSVM
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import io.github.mandar2812.dynaml.optimization.{GPMLOptimizer, GridSearch}
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import io.github.mandar2812.dynaml.pipes.{StreamDataPipe, DynaMLPipe, DataPipe}
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import org.apache.log4j.Logger
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/**
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* Created by mandar on 4/3/16.
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*/
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object DaisyPowerPlant {
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def apply(kernel: LocalSVMKernel[DenseVector[Double]],
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deltaT: Int = 2, timelag:Int = 0, stepPred: Int = 3,
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num_training: Int = 150, column: Int = 7,
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opt: Map[String, String]) =
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runExperiment(kernel, deltaT, timelag,
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stepPred, num_training, column, opt)
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def runExperiment(kernel: LocalSVMKernel[DenseVector[Double]],
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deltaT: Int = 2, timelag:Int = 0, stepPred: Int = 3,
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num_training: Int = 150, column: Int = 7,
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opt: Map[String, String]): Seq[Seq[AnyVal]] = {
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//Load Omni data into a stream
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//Extract the time and Dst values
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val logger = Logger.getLogger(this.getClass)
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val names = Map(6 -> "steam pressure",
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7 -> "main stem temperature",
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8 -> "reheat steam temperature")
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//pipe training data to model and then generate test predictions
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//create RegressionMetrics instance and produce plots
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val modelTrainTest =
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(trainTest: ((Stream[(DenseVector[Double], Double)],
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Stream[(DenseVector[Double], Double)]),
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(DenseVector[Double], DenseVector[Double]))) => {
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val model = new DLSSVM(trainTest._1._1, num_training, kernel)
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val gs = opt("globalOpt") match {
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case "GS" => new GridSearch[model.type](model)
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.setGridSize(opt("grid").toInt)
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.setStepSize(opt("step").toDouble)
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.setLogScale(false)
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case "ML" => new GPMLOptimizer[DenseVector[Double],
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Stream[(DenseVector[Double], Double)],
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DLSSVM](model)
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}
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val startConf = kernel.state ++ Map("regularization" ->
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opt("regularization").toDouble)
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val (_, conf) = gs.optimize(startConf, opt)
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model.setRegParam(opt("regularization").toDouble).learn()
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val res = trainTest._1._2.map(testpoint => (model.predict(testpoint._1), testpoint._2))
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val scoresAndLabelsPipe = DataPipe((list: List[(Double, Double)]) =>
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list.map{l => (l._1*trainTest._2._2(-1) + trainTest._2._1(-1),
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l._2*trainTest._2._2(-1) + trainTest._2._1(-1))})
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val scoresAndLabels = scoresAndLabelsPipe.run(res.toList)
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val metrics = new RegressionMetrics(scoresAndLabels,
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scoresAndLabels.length)
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metrics.setName(names(column))
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metrics.print()
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metrics.generatePlots()
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//Plotting time series prediction comparisons
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line((1 to scoresAndLabels.length).toList, scoresAndLabels.map(_._2))
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hold()
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line((1 to scoresAndLabels.length).toList, scoresAndLabels.map(_._1))
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legend(List("Time Series", "Predicted Time Series (one hour ahead)"))
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unhold()
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Seq(
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Seq(deltaT, 1, num_training, 200-num_training,
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metrics.mae, metrics.rmse, metrics.Rsq,
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metrics.corr, metrics.modelYield)
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)
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}
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val preProcessPipe = DynaMLPipe.fileToStream >
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DynaMLPipe.trimLines >
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DynaMLPipe.replaceWhiteSpaces >
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DynaMLPipe.extractTrainingFeatures(
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List(0,column,1,2,3,4,5),
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Map()
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) >
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DynaMLPipe.removeMissingLines >
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StreamDataPipe((line: String) => {
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val splits = line.split(",")
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val timestamp = splits.head.toDouble
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val feat = DenseVector(splits.tail.map(_.toDouble))
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(timestamp, feat)
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}) >
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DynaMLPipe.deltaOperationVec(deltaT)
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val trainTestPipe = DynaMLPipe.duplicate(preProcessPipe) >
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DynaMLPipe.splitTrainingTest(num_training, 200-num_training) >
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DynaMLPipe.gaussianStandardization >
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DataPipe(modelTrainTest)
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trainTestPipe.run(("data/powerplant.csv",
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"data/powerplant.csv"))
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}
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}

‎src/main/scala/io/github/mandar2812/dynaml/examples/FSExperiment.scala

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/*
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Licensed to the Apache Software Foundation (ASF) under one
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or more contributor license agreements. See the NOTICE file
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distributed with this work for additional information
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regarding copyright ownership. The ASF licenses this file
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to you under the Apache License, Version 2.0 (the
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"License"); you may not use this file except in compliance
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with the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing,
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software distributed under the License is distributed on an
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"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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KIND, either express or implied. See the License for the
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specific language governing permissions and limitations
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under the License.
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* */
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package io.github.mandar2812.dynaml.examples
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import java.io.File

‎src/main/scala/io/github/mandar2812/dynaml/examples/PreprocessAdult.scala

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/*
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Licensed to the Apache Software Foundation (ASF) under one
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or more contributor license agreements. See the NOTICE file
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distributed with this work for additional information
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regarding copyright ownership. The ASF licenses this file
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to you under the Apache License, Version 2.0 (the
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"License"); you may not use this file except in compliance
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with the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing,
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software distributed under the License is distributed on an
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"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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KIND, either express or implied. See the License for the
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specific language governing permissions and limitations
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under the License.
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* */
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package io.github.mandar2812.dynaml.examples
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import java.io.BufferedReader

‎src/main/scala/io/github/mandar2812/dynaml/examples/PreprocessForestCover.scala

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/*
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Licensed to the Apache Software Foundation (ASF) under one
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or more contributor license agreements. See the NOTICE file
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distributed with this work for additional information
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regarding copyright ownership. The ASF licenses this file
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to you under the Apache License, Version 2.0 (the
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"License"); you may not use this file except in compliance
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with the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing,
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software distributed under the License is distributed on an
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"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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KIND, either express or implied. See the License for the
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specific language governing permissions and limitations
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under the License.
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* */
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package io.github.mandar2812.dynaml.examples
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import java.io.{BufferedReader, FileInputStream, InputStreamReader}

‎src/main/scala/io/github/mandar2812/dynaml/examples/PreprocessSusy.scala

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/*
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Licensed to the Apache Software Foundation (ASF) under one
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or more contributor license agreements. See the NOTICE file
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distributed with this work for additional information
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regarding copyright ownership. The ASF licenses this file
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to you under the Apache License, Version 2.0 (the
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"License"); you may not use this file except in compliance
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with the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing,
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software distributed under the License is distributed on an
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"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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KIND, either express or implied. See the License for the
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specific language governing permissions and limitations
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under the License.
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* */
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package io.github.mandar2812.dynaml.examples
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import java.io.{BufferedReader, FileInputStream, InputStreamReader}

‎src/main/scala/io/github/mandar2812/dynaml/examples/TestAdult.scala

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/*
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Licensed to the Apache Software Foundation (ASF) under one
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or more contributor license agreements. See the NOTICE file
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distributed with this work for additional information
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regarding copyright ownership. The ASF licenses this file
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to you under the Apache License, Version 2.0 (the
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"License"); you may not use this file except in compliance
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with the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing,
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software distributed under the License is distributed on an
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"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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KIND, either express or implied. See the License for the
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specific language governing permissions and limitations
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under the License.
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* */
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package io.github.mandar2812.dynaml.examples
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import java.io.File

‎src/main/scala/io/github/mandar2812/dynaml/examples/TestCommitteeNNOmni.scala

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/*
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Licensed to the Apache Software Foundation (ASF) under one
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or more contributor license agreements. See the NOTICE file
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distributed with this work for additional information
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regarding copyright ownership. The ASF licenses this file
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to you under the Apache License, Version 2.0 (the
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"License"); you may not use this file except in compliance
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with the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing,
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software distributed under the License is distributed on an
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"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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KIND, either express or implied. See the License for the
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specific language governing permissions and limitations
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under the License.
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* */
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package io.github.mandar2812.dynaml.examples
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