Comments for Mathematica for prediction algorithms
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Using Mathematica implementations of machine learning algorithms
Fri, 07 Sep 2018 00:25:58 +0000
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Comment on Directional quantile envelopes by Anton Antonov Antonov
https://mathematicaforprediction.wordpress.com/2014/11/03/directional-quantile-envelopes/comment-page-1/#comment-1159
Fri, 07 Sep 2018 00:25:58 +0000http://mathematicaforprediction.wordpress.com/?p=430#comment-1159Thank you for your note! I fixed the wording of corresponding step 2 in the algorithm description.
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Comment on Directional quantile envelopes by Johana
https://mathematicaforprediction.wordpress.com/2014/11/03/directional-quantile-envelopes/comment-page-1/#comment-1158
Thu, 06 Sep 2018 23:43:13 +0000http://mathematicaforprediction.wordpress.com/?p=430#comment-1158Which represents k?
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Comment on A monad for Quantile Regression workflows by QRMon for some credit risk article | Mathematica for prediction algorithms
https://mathematicaforprediction.wordpress.com/2018/08/01/a-monad-for-quantile-regression-workflows/comment-page-1/#comment-1143
Fri, 24 Aug 2018 19:13:55 +0000http://mathematicaforprediction.wordpress.com/?p=984#comment-1143[…] Anton Antonov, "A monad for Quantile Regression workflows", (2018), MathematicaForPrediction at […]
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Comment on Applying Artificial Intelligence and Machine Learning to Finance and Technology by QRMon for some credit risk article | Mathematica for prediction algorithms
https://mathematicaforprediction.wordpress.com/2018/02/21/applying-artificial-intelligence-and-machine-learning-to-finance-and-technology/comment-page-1/#comment-1142
Fri, 24 Aug 2018 19:13:45 +0000http://mathematicaforprediction.wordpress.com/?p=951#comment-1142[…] (I saw the article [1] while browsing LinkedIn today. I met one of the authors during the event "Data Science Salon Miami Feb 2018".) […]
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Comment on Finding local extrema in noisy data using Quantile Regression by A monad for Quantile Regression workflows | Mathematica for prediction algorithms
https://mathematicaforprediction.wordpress.com/2015/09/27/finding-local-extrema-in-noisy-data-using-quantile-regression/comment-page-1/#comment-1126
Wed, 01 Aug 2018 10:26:26 +0000http://mathematicaforprediction.wordpress.com/?p=501#comment-1126[…] easily construct semi-symbolic algorithms for finding local extrema in noisy time series data; see [AA5]. The QRMon function with such an algorithm is […]
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Comment on Estimation of conditional density distributions by A monad for Quantile Regression workflows | Mathematica for prediction algorithms
https://mathematicaforprediction.wordpress.com/2014/01/13/estimation-of-conditional-density-distributions/comment-page-1/#comment-1125
Wed, 01 Aug 2018 10:26:20 +0000http://mathematicaforprediction.wordpress.com/?p=225#comment-1125[…] The solution of this problem using Quantile Regression is discussed in detail in [PG1] and [AA4]. […]
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Comment on A monad for classification workflows by A monad for Quantile Regression workflows | Mathematica for prediction algorithms
https://mathematicaforprediction.wordpress.com/2018/05/15/a-monad-for-classification-workflows/comment-page-1/#comment-1124
Wed, 01 Aug 2018 10:26:05 +0000http://mathematicaforprediction.wordpress.com/?p=967#comment-1124[…] The section "Implementation notes" just says that QRMon’s development process and this document follow the ones of the classifications workflows monad ClCon, [AA6]. […]
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Comment on Quantile regression with B-splines by A monad for Quantile Regression workflows | Mathematica for prediction algorithms
https://mathematicaforprediction.wordpress.com/2014/01/01/quantile-regression-with-b-splines/comment-page-1/#comment-1123
Wed, 01 Aug 2018 10:25:58 +0000http://mathematicaforprediction.wordpress.com/?p=207#comment-1123[…] 30% of the points are above that curve. This is done with Quantile Regression, see [Wk2, CN1, AA2, AA3]. Quantile Regression is a method to estimate the variable relations for all parts of the […]
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Comment on Quantile regression through linear programming by A monad for Quantile Regression workflows | Mathematica for prediction algorithms
https://mathematicaforprediction.wordpress.com/2013/12/16/quantile-regression-through-linear-programming/comment-page-1/#comment-1122
Wed, 01 Aug 2018 10:25:55 +0000http://mathematicaforprediction.wordpress.com/?p=151#comment-1122[…] say, 30% of the points are above that curve. This is done with Quantile Regression, see [Wk2, CN1, AA2, AA3]. Quantile Regression is a method to estimate the variable relations for all parts of the […]
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Comment on Quantile regression through linear programming by Thad
https://mathematicaforprediction.wordpress.com/2013/12/16/quantile-regression-through-linear-programming/comment-page-1/#comment-1117
Thu, 12 Jul 2018 01:39:48 +0000http://mathematicaforprediction.wordpress.com/?p=151#comment-1117I read the description in the package and Anton’s Quantile Regression doesn’t take more than one independent variable. I apologise for my silly recommendation. {;^)
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