Real World Temporal Anomaly Detection through Supervised Machine Learning and Set Theory
Last Updated on August 18, 2023 by Editorial Team
Author(s): Ashutosh Malgaonkar
Originally published on Towards AI.
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Explore Open Data from the City of Seattle
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