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input {
	stdin {
  }
}

filter {
     csv {
        columns => ["timestamp","value"]
		separator => ","
        convert => { 'value' => 'float' }

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#!/usr/bin/env bash

#These should be deprecated when things are moved out of the protocol package
./gradlew x-pack:protocol:checkStyle
./gradlew x-pack:protocol:test

./gradlew :client:rest-high-level:checkStyle
./gradlew :client:rest-high-level:test

./gradlew :client:rest-high-level:integTest -Dtests.class=org.elasticsearch.client.documentation.MlClientDocumentationIT

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{
    "configurations": [
        {
            "name": "Mac",
            "includePath": [
                "${workspaceFolder}/**",
                "/usr/local/include/boost-1_65_1/",
                "/usr/local/include",
                "/usr/include"
            ]

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PUT _template/template_test
{
  "index_patterns": ["test*"],
  "settings": {
    "number_of_shards": 1
  },
  "mappings": {
    "doc": {
      "dynamic_templates": [
          {

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f=load(FILENAME.mat)
C = [f.X, f.y]
csvwrite(FILENAME.csv, C)

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PUT test-bool/
{
  "mappings" : {
      "_doc" : {
        "properties" : {
          "my-field" : {
            "type" : "boolean"
        }, "my-terms": {
          "type" : "keyword"
        }

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PUT _scripts/linear_regression_inference
{
  "script": {
    "lang": "painless",
    "source": """
    double total = params.intercept;
    for (int i = 0; i < params.coefs.length; ++i) {
      total += params.coefs.get(i) * doc[params['x'+i]].value;
    }
    return total;

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import xgboost as xgb
from sklearn import datasets
from sklearn.metrics import mean_squared_error
import m2cgen as m2c


diabetes = datasets.load_diabetes() # load data
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(diabetes.data, diabetes.target, test_size=0.2, random_state=0)
print(diabetes.feature_names)

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import java.util.AbstractMap;
import java.util.ArrayList;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.regex.Pattern;

/**
 * This class contains the parsing logic for implementing the DRAIN algorithm.

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{
  "listings-ash" : {
    "aliases" : { },
    "mappings" : {
      "_meta" : {
        "created_by" : "ml-file-data-visualizer"
      },
      "properties" : {
        "@timestamp" : {
          "type" : "date"