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---
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tags:
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- other
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- sensor
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---
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Part of MONSTER: <https://arxiv.org/abs/2502.15122>.
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***FordChallenge*** is obtained from Kaggle and consists of data from 600 real-time driving sessions, each lasting approximately 2 minutes and sampled at 100ms intervals [1]. These sessions include trials from 100 drivers of varying ages and genders. The dataset contains 8 physiological, 11 environmental, and 11 vehicular measurements, with specific details such as names and units undisclosed by the challenge organizers. Each data point is labeled with a binary outcome: 0 for "distracted" and 1 for "alert". The objective of the challenge is to design a classifier capable of accurately predicting driver alertness using the provided physiological, environmental, and vehicular data.
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[1] Mahmoud Abou-Nasr. (2011). Stay Alert! The Ford Challenge. <https://kaggle.com/competitions/stayalert>. Kaggle.
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---
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tags:
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- time series
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- time series classification
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- monster
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- other
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- sensor
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license: other
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pretty_name: FordChallenge
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size_categories:
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- 10K<n<100K
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Part of MONSTER: <https://arxiv.org/abs/2502.15122>.
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|FordChallenge||
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|Category|Sensor|
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|Num. Examples|36,257|
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|Num. Channels|30|
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|Length|40|
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|Sampling Freq.|10 Hz|
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|Num. Classes|2|
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|License|Other|
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|Citations|[1]|
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***FordChallenge*** is obtained from Kaggle and consists of data from 600 real-time driving sessions, each lasting approximately 2 minutes and sampled at 100ms intervals [1]. These sessions include trials from 100 drivers of varying ages and genders. The dataset contains 8 physiological, 11 environmental, and 11 vehicular measurements, with specific details such as names and units undisclosed by the challenge organizers. Each data point is labeled with a binary outcome: 0 for "distracted" and 1 for "alert". The objective of the challenge is to design a classifier capable of accurately predicting driver alertness using the provided physiological, environmental, and vehicular data.
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[1] Mahmoud Abou-Nasr. (2011). Stay Alert! The Ford Challenge. <https://kaggle.com/competitions/stayalert>. Kaggle.
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