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3 answers

XGboost - Choice made by model

i am using XGboost to predict a 2 classes target variable on insurance claims. I have a model ( training with cross validation, hyper parameters tuning etc...) i run on another dataset. My question is : is there a way to know why a given claim has…
Fabrice BOUCHAREL
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Is this a good practice of feature engineering?

I have a practical question about feature engineering... say I want to predict house prices by using logistic regression and used a bunch of features including zip code. Then by checking the feature importance, I realize zip is a pretty good…
user3768495
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NN embedding layer

Several neural network libraries such as tensorflow and pytorch offer an Embedding layer. Having implemented word2vec in the past, I understand the reasoning behind wanting a lower dimensional representation. However, it would seem the embedding…
cbake
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How to train the same RNN over multiple series?

I have multiple separate time series and would like to train the same LSTM network on them. How to do in this situation? I can't just concatenate timeseries (along time), because I am afraid network will be confused by jumps at the points of…
Dims
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In which epoch should i stop the training to avoid overfitting

I'm working on an age estimation project trying to classify a given face in a predefined age range. For that purpose I'm training a deep NN using the keras library. The accuracy for the training and the validation sets is shown in the graph…
Yiannis Ath
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Assumptions of linear regression

In simple terms, what are the assumptions of Linear Regression? I just want to know that when I can apply a linear regression model to our dataset.
Anvay Joshi
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How to draw convolutional neural network diagrams?

I have to draw a CNN diagram similar to this: I tried all the tools mentioned in https://datascience.stackexchange.com/a/14900, but there is no easy way to do it. Is there any automated way to do it? Or do I have to do it manually. In addition, is…
Beginner
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Debugging Neural Networks

I've built an artificial neural network in python using the scipy.optimize.minimize (Conjugate gradient) optimization function. I've implemented gradient checking, double checked everything etc and I'm pretty certain it's working correctly. I've run…
user3726050
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AUC-ROC of a random classifier

Why the area under the ROC Curve for a random classifier is equal to 0.5 and has diagonal shape? For me a random classifier would have 25% of TP,TN,FP,FN and therefore it would only be a single point on the ROC Curve.
Victor
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weighted cross entropy for imbalanced dataset - multiclass classification

I am trying to classify images to more then a 100 classes, of different sizes ranged from 300 to 4000 (mean size 1500 with std 600). I am using a pretty standard CNN where the last layer outputs a vector of length number of classes, and using…
Itaysason
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Why do we use gradients instead of residuals in Gradient Boosting?

I have found mentions of two advantages in using gradients instead of actual residuals: 1) Using gradients will allow us to plug in any loss function (not just mse) without having to change our base learners to make them compatible with the loss…
eyio
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Multicollinearity in Decision Tree

Can anybody please explain the affect of multicollinearity on Decision Tree algorithms (Classification and regression). I have done some searching but was not able to find the right answer as some say it affects it and others say it doesn't.
deepguy
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Validation showing huge fluctuations. What could be the cause?

I'm training a CNN for a 3-class image classification problem. My training loss decreased smoothly, which is the expected behaviour. However, my validation loss shows a lot of fluctuation. Is this something that I should be worried about, or should…
Josh
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Clustering customer data stored in ElasticSearch

I have a bunch of customer profiles stored in a elasticsearch cluster. These profiles are now used for creation of target groups for our email subscriptions. Target groups are now formed manually using elasticsearch faceted search capabilities…
Konstantin V. Salikhov
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How does the bounding box regressor work in Fast R-CNN?

In the fast R-CNN paper (https://arxiv.org/abs/1504.08083) by Ross Girshick, the bounding box parameters are continuous variables. These values are predicted using regression method. Unlike other neural network outputs, these values do not represent…
Saptarshi Roy
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