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From: Greg KH <greg@kroah.com>
To: prathamesh naik <prathamesh.naik20@gmail.com>
Cc: "Valdis Klētnieks" <valdis.kletnieks@vt.edu>,
	kernelnewbies@kernelnewbies.org
Subject: Re: Predicting Process crash / Memory utlization using machine learning
Date: Thu, 10 Oct 2019 09:17:58 +0200
Message-ID: <20191010071758.GB258938@kroah.com> (raw)
In-Reply-To: <CAGG2BF79aHZOvw+1nG5RW32w7hX3HyGp1eB8t9Rr1G2N1ZR4Vg@mail.gmail.com>

On Wed, Oct 09, 2019 at 04:40:45PM -0700, prathamesh naik wrote:
> Thanks a lot for sharing.
> One of the problem I am facing is not having enough actual data. I can
> create simulated data but it is overfitting my algorithm.
> Second problem is I am not sure what all factors (called features in ML
> terms) are useful for pattern creation.
> Some of the factors I could think of were :
> 1. Memory used
> 2. CPU
> 3. shared memory
> 4. vmstat
> 5. message queue sizes

There are loads and loads of things you can monitor in a system.  See
any of the talks by Brendan Gregg http://www.brendangregg.com/ for lots
of examples.

good luck!

greg k-h

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Thread overview: 5+ messages / expand[flat|nested]  mbox.gz  Atom feed  top
2019-10-09  8:23 prathamesh naik
2019-10-09 21:28 ` Valdis Klētnieks
2019-10-09 23:40   ` prathamesh naik
2019-10-10  7:17     ` Greg KH [this message]
2019-10-10  8:23 ` Ruben Safir

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