# Classifier indefinitely skips prediction on certain classes **URL:** \ **Category:** DL4J\ **Created:** [February 14, 2023, 5:09am UTC](https://community.konduit.ai/t/classifier-indefinitely-skips-prediction-on-certain-classes/2240 "2023-02-14T05:09:50Z")\ **Posts on this page:** 1\ **Showing post:** 4
**Author:** ![agibsonccc](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/agibsonccc/32/697_2.png) [@agibsonccc](https://community.konduit.ai/u/agibsonccc)\ **Post date:** [February 14, 2023, 12:24pm UTC](https://community.konduit.ai/t/classifier-indefinitely-skips-prediction-on-certain-classes/2240/4 "2023-02-14T12:24:26Z")
@chapipo this is a \> 4 year old tutorial.Please avoid older content like that. Some initial tips here: your learning rate is very high. Change that to be lower. There’s almost no reason to have 5 dense layers. Reduce your number of layers to just 1 and see how your results are first. By “1” I mean 1 Dense Layer and 1 output layer. Follow these pages for some more tips: > **[Tuning and Training](https://deeplearning4j.konduit.ai/deeplearning4j/how-to-guides/tuning-and-training)** Ensure your data is normalized if needed as well. (This is needed if it’s not values between 0 and 1.) Search around on the forums for post like this: > [@How to data normalization for INDArray/Array](https://community.konduit.ai/t/how-to-data-normalization-for-indarray-array/184): > > val model = modelLoadHDFS("hdfs://xx/tmp/mutiTimestepsLstm.h5") val myArray = new Array[Float](size) ..... val xx = splitSequence(myArray , 5, 1) val myINDArray = xx(0).asInstanceOf[INDArray] val pridictOut = model.output(myINDArray) How to data normalization for myINDArray or my myArray ? Thanks. if the docs aren’t helping you. Feel free to ask clarifying questions as well. --- _[View the full topic](https://community.konduit.ai/t/classifier-indefinitely-skips-prediction-on-certain-classes/2240)._