Going to war with the giants_ automated machine learning with mljar

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Herein the performance of MLJAR on Kaggle dataset from “Give me some credit” challenge is reported. Learning articles The obtained results are compared with other predictive APIs from Amazon, Google, PredicSis and BigML. Cnbc stock market futures This post was inspired with Louis Dorard’s article.


Gbp to usd rate Dataset

The dataset used in this article is from Kaggle website and can be downloaded from here. Pound exchange rate There are 150,000 samples in training dataset with 10 input attributes and binary target. Us stock market futures live The distributions and attributes’ types are presented in picture below. Aed to usd chart There are no categorical values in the dataset, however there are missing values in the dataset – they will be handled automatically by MLJAR and filled with median values. Gbp to usd yahoo There is no additional preprocessing applied. Cool pictures The testing dataset from this competition has 101,503 samples (their values are not used for missing values imputation in training dataset). Jpy usd yahoo This dataset will be used for computing predictions, which will be submitted to Kaggle scoring system.

Each algorithm is tuned separately – this include training and hyper-parameter search. Binary representation Additionally, from all trained models an ensemble of models is created. Dollar rate today in india Models are trained with 10 fold stratified cross validation on training dataset. Binary search javascript The Area Under ROC Curve (AUC) metric is used to measure classifier’s performance. Usd euro chart Results

The results are summarized in table below. Gold price history chart 100 years The highest AUC was obtained by ensemble of models. Yahoo futures indices The best single algorithm performance was obtained by Xgboost. Usa today Surprisingly, Neural Networks have the poorest performance – just a little above than random classifier. Rmb usd This is probably the effect of missing proper scaling of input features.

For algorithms like: Xgboost, Random Forest and Extra Trees there is available information about features importance – it was presented in the figure 2. 100 eur to usd It can be observed that there is no single feature that dominates for all algorithms – this is because each algorithm uses features differently. Dow jones futures exchange That is why, the ensemble of all algorithms improves the overall performance.

In Louis Dorard’s article the performance of predictive APIs from Amazon, Google, PredicSis and BigML is compared. Stock connect china Herein, we add to this comparison a performance from MLJAR. Today’s futures market All results are presented in table 2. Cad usd exchange rate The MLJAR is the most accurate, however its training and testing time are quite high – because MLJAR searches for the best model for each learning algorithm. Rub usd converter As the result there were 69 models trained in total. Litecoin charts Based on these models the ensemble was created from 16 selected models. Usd jpy chart The prediction time is also high because it is prediction from ensemble of models. Market futures yahoo The results of Amazon, Google, PredicSis, BigML are from Louis Dorard’s article, where he trained algorithms on 90% of train data and validate on 10% train data and prediction times are computed on 5k samples. Usd to zar exchange rate history Herein, MLJAR was trained on 10 fold CV on full train dataset and prediction time is for full test set, which is 101k samples.

In Louis Dorard’s article there was an approximate rank in the Kaggle competition assessed. What is the futures market We present below approximate Kaggle rank in this competition for compared APIs, however for MLJAR rank was computed by Kaggle scoring system:

This comparison gives some taste of how MLJAR can be used in data analysis. Binary search tree program in c It is slower than other services (Google, Amazon, PredicSis, BigML) because it learns several models for each algorithm. Gender pregnancy Therefore MLJAR can find the most accurate model. Exchange rate usd to inr The speed of the MLJAR training can be easily improved by adding more machines for training (which is now 4 machines with 8CPU and 15 GB RAM per user). Stock market trading hours new years eve The MLJAR project with all results is public and can be accessed from here. Eur usd news today There is a youtube video from project creation available in this link.

Bio: Piotr Płoński is a founder of MLJAR. Rate of exchange usd to zar He is also assistant professor at Warsaw Univerisity of Technology, where he applies machine learning methods to analyze high energy physics data from neutrino experiments.

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