Github user JeremyNixon commented on the issue:
https://github.com/apache/spark/pull/13617
@avulanov Great to hear from you! I'd love to give you a short tour of
MLPR's use cases.
@jkbradley Wonderful to hear that you agree this should get in, and I'm
happy to provide a few applications and results from academia and industry.
1. Computer Vision
a. Object Localization / Detection as DNN Regression
b. Human Pose Regression
2. Finance
a. Currency Exchange Rate
b. Stock Price Prediction
c. Forecasting Financial Time Series
d. Crude Oil Price Prediction
3. Atmospheric Sciences
a. Air Quality Prediction
b. Carbon Dioxide Pollution Prediction
c. Ozone Concentration Modeling
d. Sulphur Dioxide Concentration Prediction
4. Infrastructure
a. Road Tunnel Cost Estimation
b. Highway Engineering Cost Estimation
5. Geology / Physics
a. Meteorology and Oceanography Applications
b. Pacific Sea Surface Temperature Prediction
c. Hydrological Modeling
6. Summary
## Computer Vision
(Assumes we include convolutional and pooling layer types)
#### Detection as DNN Regression - Object Localization Detection
Precise object localization is necessary to track an objectâs shape or
movement. Includes a regression layer which generates an object binary mask, a
binary representation of the object in the image. This creates an object
detector, learning the location of an object or even specific parts of an
object in an image.
http://papers.nips.cc/paper/5207-deep-neural-networks-for-object-detection.pdf
#### ImageNet winning solution for Object Localization
Overfeat: http://arxiv.org/pdf/1312.6229v4.pdf
It would be nice to support multiple outputs for an application like object
localization -
â4.2, Regressor Training: The regression network takes as input the
pooled feature maps from layer 5. It has 2 fully-connected hidden layers of
size 4096 and 1024 channels, respectively. The final output layer has 4 units
which specify the coordinates for the bounding box edges.â
#### Pose Regression
Estimate the pose of humans in video, results significantly better than the
previous state of the art. Able to detect sign language, generalizes to finding
the location of elbows/hands/head etc.
https://www.robots.ox.ac.uk/~vgg/publications/2014/Pfister14a/pfister14a.pdf
## Finance
#### Currency Exchange Rate
Neural Network Regression for forecasting the exchange rate between
currencies. NN outperforms standard ARIMA methodology for forecasting.
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.52.2442
Accurate Currency Exchange Rate Forecasting using MLPR
http://liawww.epfl.ch/uploads/project_reports/report_282.pdf
#### Stock Price Prediction: Comparison of Methods
Neural Network Regression outperforms other regression methods in stock
price prediction.
https://arxiv.org/pdf/1003.1457.pdf
#### Forecasting Financial Time Series
Applying deep regression networks to forecast market prices.
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.15.8688&rep=rep1&type=pdf
#### Crude Oil Price Prediction
Spot price forecasting for world crude oil.
http://www.sciencedirect.com/science/article/pii/S0140988308000765
## Atmospheric Sciences
#### Overview
There are numerous applications across the atmospheric sciences, where
highly nonlinear relationships need to be appropriately modeled.
https://www.researchgate.net/publication/263416087_Artificial_Neural_Networks_The_Multilayer_Perceptron_-_A_Review_of_Applications_in_the_Atmospheric_Sciences
#### Air Quality Prediction
Modeling nonlinear relationship between meteorology and pollution for
surface ozone concentrations in industrialized areas.
https://www.researchgate.net/profile/VR_Prybutok/publication/8612909_Prybutok_R._A_neural_network_model_forecasting_for_prediction_of_daily_maximum_ozone_concentration_in_an_industrialized_urban_area._Environ._Pollut._92(3)_349-357/links/0deec53babcab9c32f000000.pdf
#### Air Pollution Prediction - Carbon Dioxide
Neural Network Regression outperforms multiple linear regression for carbon
dioxide air pollution prediction in China.
http://202.116.197.15/cadalcanton/Fulltext/21276_2014319_102457_186.pdf
#### Atmospheric Sulphur dioxide concentrations
Many applications of Neural Network Regression to air pollution, including
predicting sulfur dioxide concentration.
http://cdn.intechweb.org/pdfs/17396.pdf
#### Ozone Concentration Comparison
Neural Networks for Regression outperform decision trees and linear
regression for modeling nonlinear relationships required to predict ozone
concentration.
https://www.researchgate.net/publication/263416130_Statistical_Surface_Ozone_Models_An_Improved_Methodology_to_Account_for_Non-Linear_Behaviour
## Infrastructure
#### Road Tunnel Cost Estimation
Regression Neural Network leads to accurate cost estimation for road
tunnels.
http://ascelibrary.org/doi/abs/10.1061/(ASCE)CO.1943-7862.0000479
#### Highway Engineering Cost Estimation
Neural Networks reliably predict the cost of highway construction projects.
http://www.jcomputers.us/vol5/jcp0511-19.pdf
## Geophysics
#### Pacific Sea Surface Temperature
Surface temperature prediction environments are nonlinear. Presentation of
an MLPR outperforming linear regression models over the domain.
http://www.ncbi.nlm.nih.gov/pubmed/16527455
#### Meteorology and Oceanography
Improving neural network methods for many tasks in meteorology and
oceanography, including seasonal climate forecasting, various time series,
satellite imagery analysis, ocean acoustics and more.
https://open.library.ubc.ca/cIRcle/collections/facultyresearchandpublications/32536/items/1.0041821
#### Hydrological Modeling
River flow forecasting from satellite data with neural networks.
http://hydrol-earth-syst-sci.net/13/1607/2009/hess-13-1607-2009.pdf
Modeling of nonlinear hydrological relationships for river basin
(watershed) management.
http://jh.iwaponline.com/content/ppiwajhydro/10/1/3.full.pdf
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