Just apply LIME to explain, trust and validate your predictions for any ML model

[@hewramanwaran6444]

Thank you very much for your excellent explanation.

[@praveenkumarchandaliya1900]

Generally, image channels have three (RGB). If we try to concrete more than two color models, then the channels of the image is more than 3, means 6,9,12...How we can use LIME on more than three-channel images.

[@daminibabbar1782]

Hey just a great explanation, can i get more clarity on how the weights are computed and the linear model is being fitted?

[@wakeupsahitya]

Sir could you please tell how can I set the color pallette for LIME

[@حسنينالزركاني-ث1د]

Thanks you 😘

[@650AILab]

Thank you too

[@educationgist7798]

thanks sir

[@650AILab]

So nice of you

[@minhaoling3056]

How many dataset you used ?

[@650AILab]

Remember you are using LIME to explain the model results. So the LIME interpretation library is used on top of your generated model so the original dataset used to generate the model (which you are using for scoring and prediction) will be the dataset for the LIME explanation as well.

[@minhaoling3056]

@@650AILab will using small dataset on the original model affect the lime explainability?