blob: 89564007e0e2d11363682bbb2634da36a66f1b99 [file] [log] [blame]
#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
ams_iforest <- function(url, train_start, train_end, test_start, test_end, threshold_score) {
res <- get_data(url)
num_metrics <- length(res$metrics)
anomalies <- data.frame()
metricname <- res$metrics[[1]]$metricname
data <- data.frame(as.numeric(names(res$metrics[[1]]$metrics)), as.numeric(res$metrics[[1]]$metrics))
names(data) <- c("TS", res$metrics[[1]]$metricname)
for (i in 2:num_metrics) {
metricname <- res$metrics[[i]]$metricname
df <- data.frame(as.numeric(names(res$metrics[[i]]$metrics)), as.numeric(res$metrics[[i]]$metrics))
names(df) <- c("TS", res$metrics[[i]]$metricname)
data <- merge(data, df)
}
algo_data <- data[ which(df$TS >= train_start & df$TS <= train_end) , ][c(1:num_metrics+1)]
iForest <- IsolationTrees(algo_data)
test_data <- data[ which(df$TS >= test_start & df$TS <= test_end) , ]
if_res <- AnomalyScore(test_data[c(1:num_metrics+1)], iForest)
for (i in 1:length(if_res$outF)) {
index <- test_start+i-1
if (if_res$outF[i] > threshold_score) {
anomaly <- c(test_data[i,1], if_res$outF[i], if_res$pathLength[i])
anomalies <- rbind(anomalies, anomaly)
}
}
if(length(anomalies) > 0) {
names(anomalies) <- c("TS", "Anomaly Score", "Path length")
}
return (anomalies)
}