Real World Temporal Anomaly Detection through Supervised Machine Learning and Set Theory

Author(s): Ashutosh Malgaonkar

Originally published on Towards AI.

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Table Of Contents:

I. The Problem Statement

II. Remodeling time series into a supervised problem

III. Supervised Modeling and Analysis

I. Problem Statement

The data can be downloaded from here: Seattle Burke Gilman Trail U+007C Kaggle

The essence of this problem statement is that we need to detect anomalies 3 hours in advance. An anomaly is defined as >500 total people on the trail 3 hours from now. In order to solve this problem, we have been given per-hour data of trail traffic — pedestrian and bike.

II. Remodeling… Read the full blog for free on Medium.

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Published via Towards AI