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I wish someone built something like this for generic classification. You give the system a bunch of folders. Each folder is a label containing corresponding sam

I wish someone built something like this for generic classification. You give the system a bunch of folders. Each folder is a label containing corresponding samples. The system then creates a replica of the folder structure with no content. Each time you give it a new piece of data it places it in one of those newly created folders. This is an interface truly anyone could use. Just call it "intelligent folders" or something. The user doesn't even need to know which algorithm it uses. Just split sample into training and test data at random and choose the algo that give best results. I was working on this for text data, but then switched jobs and don't have energy to make this in my spare time right now.

bryanrasmussen 8y ago
LingPipe http://alias-i.com/lingpipe/ http://alias-i.com/lingpipe/ had an example that did this IIRC it was their newsgroup example http://alias-i.com/lingpipe/demos/tutorial/classify/read-me.html http://alias-i.com/lingpipe/demos/tutorial/classify/read-me...., I adapted it in to running a trial classification of Danish Laws. I remember I had greater than 80% precision without fiddling with settings and for less than a days worth of work setting up, don't remember the recall but it was also pretty reasonable.
_mme 8y ago
I built something similar for images. It's command line based, so one could simply create a bash script to copy data to a folder based on a prediction. https://github.com/vergeml/vergeml https://github.com/vergeml/vergeml
pplonski86 8y ago
I'm thinking about such a thing but for databases. "Intelligent table" where one column is a prediction from ML. Each newly inserted row is automatically used as input for ML model and prediction is inserted into database. Maybe it will be easily extendable to work with folders.
tyingq 8y ago
Popfile does that with email and a Bayesian classifier. It might be a good thing to look at for ideas.

bryanrasmussen 8y ago

LingPipe http://alias-i.com/lingpipe/ http://alias-i.com/lingpipe/ had an example that did this IIRC it was their newsgroup example http://alias-i.com/lingpipe/demos/tutorial/classify/read-me.html http://alias-i.com/lingpipe/demos/tutorial/classify/read-me...., I adapted it in to running a trial classification of Danish Laws. I remember I had greater than 80% precision without fiddling with settings and for less than a days worth of work setting up, don't remember the recall but it was also pretty reasonable.

_mme 8y ago

I built something similar for images. It's command line based, so one could simply create a bash script to copy data to a folder based on a prediction. https://github.com/vergeml/vergeml https://github.com/vergeml/vergeml

pplonski86 8y ago

I'm thinking about such a thing but for databases. "Intelligent table" where one column is a prediction from ML. Each newly inserted row is automatically used as input for ML model and prediction is inserted into database. Maybe it will be easily extendable to work with folders.

tyingq 8y ago

Popfile does that with email and a Bayesian classifier. It might be a good thing to look at for ideas.