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Questions tagged [kaggle]

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14 views

Titanic Disaster Problem in Kaggle: distribution of numerical feature values across the samples

I'm still a newbie in Data Science and I found the Titanic question and solution here in Kaggle. I've been trying to understand the solution yet I still can't grasp why he used those percentiles for ...
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0answers
18 views

Issues with pandas chunk merge

I'm trying to solve a kaggle competition - https://www.kaggle.com/c/ga-customer-revenue-prediction Since the data is too much to fit in memory at once, I'm trying to clean, process and save data back ...
3
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1answer
29 views

Hyperparameter tuning for stacked models

I'm reading the following kaggle post for learning how to incorporate model stacking http://blog.kaggle.com/2016/12/27/a-kagglers-guide-to-model-stacking-in-practice/ in ML models. The structure ...
1
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1answer
18 views

Can I make kaggle kernels read directly from my computer?

For some reason jupyter notebooks never work the same as kaggle kernels for me. I want to use kaggle kernels but the downside is I don't know how to make it read from a file on the computer like a ...
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0answers
90 views

Comparing XGBR with CatBoost performance

I saw on a CatBoost site that it supposed to outperform any other boosted training model and decided to try it myself on a Kaggle's https://www.kaggle.com/c/house-prices-advanced-regression-techniques....
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0answers
104 views

How decision trees work in Python

I am new to the field of machine learning. I have just recently learnt Decision Trees and started solving Titanic Survival problem from Kaggle Competition. I understood the algorithm behind decision ...
3
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2answers
35 views

Dummy variable for Categorical values

The question is in reference to solution of Titanic survival predictionat kaggle . As many have did the similar kind of feature extraction, They have converted some of the numerical features (Age, ...
2
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3answers
39 views

When should ordinal data be represented catigorically and when as integer?

I am doing the Kaggle competition House Prices: Advanced Regression Techniques to learn more about data analysis. I would like to apply multiple models to the data(Regularized LR, Random Forests, ...
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79 views

What are techniques for encoding this data into something consumable by a logistic regression model?

I am trying to practice/learn some new data science skills by taking the now ended Allstate Purchase Prediction Challenge and seeing how well I can score. In the dataset given we see a customers ...
3
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1answer
2k views

“concat” mode can only merge layers with matching output shapes except for the concat axis

I have a function I am trying to debug which is yielding the following error message: ValueError: "concat" mode can only merge layers with matching output shapes except for the concat axis. Layer ...
0
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1answer
95 views

Why there is two output in Titanic case in tflearn quickstart?

I am stuck in the tflearn quickstart guide. I've tried tit and it works perfectly with accuracy around 78%, but the problem is I don't understand why the "labels" consist of two "survived" columns ...
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0answers
107 views

Avoid hardware limitation while competing in Kaggle?

I've learned machine learning via textbooks and examples, which don't delve into the engineering challenges of working with "big-ish" data like Kaggle's. As a specific example, I'm working on the New ...
0
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1answer
647 views

xgboost with tree_method = 'hist' in R

According to a benchmark of GBM vs. xgboost vs. LightGBM (https://www.kaggle.com/nschneider/gbm-vs-xgboost-vs-lightgbm) it is possible to implenet xgboost with the argument ...
10
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3answers
6k views

Why do we convert skewed data into a normal distribution

I was going through a solution of the Housing prices competition on Kaggle (Human Analog's Kernel on House Prices: Advance Regression Techniques) and came across this part: ...
1
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0answers
34 views

Is it possible to detect which field does a rotated “kaggle” contest data come from?

Imagine I setup a Kaggle competition with normalized stock data (e.g. price, volume, etc) plus a random rotation matrix (i.e. so that it's less obvious what the features are). Is it possible for a ...
3
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1answer
117 views

How will a rotation matrix affect contestants in machine learning contests?

Machine Learning contests like Kaggle usually layout the machine learning task in a human-understandable way. E.g. they might tell you the meaning of the input (features). But what if a Machine ...
3
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1answer
113 views

Owen Zhang's slides: what does the “time” mean?

Here is one of Owen Zhang's slideshares. At page 12, what does the time mean?
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0answers
145 views

HIgher Order Interaction Variables. How to use them in model? [closed]

http://stats.idre.ucla.edu/stata/webbooks/logistic/chapter2/ This above website gives an example about using interaction effect between variables. Interacting variables are multiplied and used in the ...
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3answers
371 views

Can you recommend a machine learning challenge that is suitable for novices?

I am looking for a challenge that is suitable for a group of novices who want to learn the basics of data science and machine learning. The challenge should match the following criteria: is based on ...
1
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1answer
598 views

How to use ensemble of models in FM or FFM?

I am using Factorization Machines ( libfm) and also the Field Aware Factorization Machines (libffm) for a kaggle competition. I am currently using the single models of each respectively for ...
0
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1answer
246 views

Titanic Disaster

I have been working on the Kaggle tutorial on the Titanic Disaster. Although I get a result which seems good to me (on the training set) the trained model performs bad on the test set. It would be ...
4
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1answer
7k views

How can I fill NaN values in a pandas data frame?

Greeting everyone. I am trying to learn data analysis and machine learning by trying out some problems. I found a competition "House prices" which is actually a playground competition. Since I am very ...
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1answer
665 views

Feature engineering using XGBoost

I am participating in a kaggle competition. I am planning to use the XGBoost package (in R). I read the XGBoost documentation and understood the basics. Can someone explain how is feature engineering ...
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2answers
177 views

Multivariate linear regression accounting for threshold / data cleaning

I am trying to make a linear regression model for the sale price of a house based on many variables (based on the data from this Kaggle challenge https://www.kaggle.com/c/house-prices-advanced-...
2
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1answer
1k views

Sklearn StratifiedKFold code explanation

While going through the following blog I came across the following code snippet ...
18
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3answers
9k views

How to perform feature engineering on unknown features?

I am participating on a kaggle competition. The dataset has around 100 features and all are unknown (in terms of what actually they represent). Basically they are just numbers. People are performing ...
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1answer
863 views

create a company to make money by winning Kaggle competition [closed]

I am thinking of creating a data science company (team) that aims to make money by winning Kaggle competitions. It will be actually a onsite data science learning service but I want to create the ...
2
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1answer
411 views

What's cooking Kaggle - Improve model

I'm participating in a Kaggle contest "What's cooking". The goal is to know wich kind of cuisine we have, depending on some ingredients. So it's a multiclass classification problem. I have an existing ...
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0answers
201 views

non-linear optimization for a linear classifier? (scikit-learn)

Using scikit-learn, why would you use bfgs optimization which is non-linear for a linear classifier as logistic regression? I am confused. Does the optimization method finds the optimum of the chosen ...
2
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1answer
309 views

Finding parameters with extreme values (classification with scikit-learn)

I am currently working with the forest cover type prediction from Kaggle, using classification models with scikit-learn. My main purpose is learning about the different models, so I don't pretend to ...
12
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1answer
5k views

Hashing Trick - what actually happens

When ML algorithms, e.g. Vowpal Wabbit or some of the factorization machines winning click through rate competitions (Kaggle), mention that features are 'hashed', what does that actually mean for the ...
8
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3answers
5k views

Why does Gradient Boosting regression predict negative values when there are no negative y-values in my training set?

As I increase the number of trees in scikit learn's GradientBoostingRegressor, I get more negative predictions, even though there are no negative values in my ...