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1500 questions
34
votes
6 answers

Gini coefficient vs Gini impurity - decision trees

The problem refers to decision trees building. According to Wikipedia 'Gini coefficient' should not be confused with 'Gini impurity'. However both measures can be used when building a decision tree - these can support our choices when splitting the…
Damien
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33
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3 answers

Hypertuning XGBoost parameters

XGBoost have been doing a great job, when it comes to dealing with both categorical and continuous dependant variables. But, how do I select the optimized parameters for an XGBoost problem? This is how I applied the parameters for a recent Kaggle…
Dawny33
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33
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4 answers

Neural Network parse string data?

So, I'm just starting to learn how a neural network can operate to recognize patterns and categorize inputs, and I've seen how an artificial neural network can parse image data and categorize the images (demo with convnetjs), and the key there is to…
MidnightLightning
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33
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6 answers

Are there any tools for feature engineering?

Specifically what I am looking for are tools with some functionality, which is specific to feature engineering. I would like to be able to easily smooth, visualize, fill gaps, etc. Something similar to MS Excel, but that has R as the underlying…
John
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33
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6 answers

Validation loss is not decreasing

I am trying to train a LSTM model. Is this model suffering from overfitting? Here is train and validation loss graph:
DukeLover
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33
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8 answers

Best practical algorithm for sentence similarity

I have two sentences, S1 and S2, both which have a word count (usually) below 15. What are the most practically useful and successful (machine learning) algorithms, which are possibly easy to implement (neural network is ok, unless the architecture…
DaveTheAl
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33
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1 answer

Ways to deal with longitude/latitude feature

I am working on a fictional dataset with 25 features. Two of the features are latitude and longitude of a place and others are pH values, elevation, windSpeed etc with varying ranges. I can perform normalization on the other features but how do I…
AllThingsScience
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33
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5 answers

How can I get a measure of the semantic similarity of words?

What is the best way to figure out the semantic similarity of words? Word2Vec is okay, but not ideal: # Using the 840B word Common Crawl GloVe vectors with gensim: # 'hot' is closer to 'cold' than 'warm' In [7]: model.similarity('hot',…
Thomas Johnson
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32
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3 answers

How can I check the correlation between features and target variable?

I am trying to build a Regression model and I am looking for a way to check whether there's any correlation between features and target variables? This is my sample dataset Loan_ID Gender Married Dependents Education Self_Employed…
Jeeth
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32
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4 answers

Role derivative of sigmoid function in neural networks

I try to understand role of derivative of sigmoid function in neural networks. First I plot sigmoid function, and derivative of all points from definition using python. What is the role of this derivative exactly? import numpy as np import…
lukassz
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32
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2 answers

How to calculate the fold number (k-fold) in cross validation?

I am confused about how I choose the number of folds (in k-fold CV) when I apply cross validation to check the model. Is it dependent on data size or other parameters?
Taimur Islam
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31
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4 answers

What algorithms should I use to perform job classification based on resume data?

Note that I am doing everything in R. The problem goes as follow: Basically, I have a list of resumes (CVs). Some candidates will have work experience before and some don't. The goal here is to: based on the text on their CVs, I want to classify…
user1769197
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31
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7 answers

Can machine learning learn a function like finding maximum from a list?

I have an input which is a list and the output is the maximum of the elements of the input-list. Can machine learning learn such a function which always selects the maximum of the input-elements present in the input? This might seem as a pretty…
user78739
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31
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3 answers

General approach to extract key text from sentence (nlp)

Given a sentence like: Complimentary gym access for two for the length of stay ($12 value per person per day) What general approach can I take to identify the word gym or gym access?
William Falcon
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31
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5 answers

Why underfitting is called high bias and overfitting is called high variance?

I have been using terms like underfitting/overfitting and bias-variance tradeoff for quite some while in data science discussions and I understand that underfitting is associated with high bias and over fitting is associated with high variance. But…
Vaibhav Thakur
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