I’m using trial version of aspose ocr .net for testing its capability to recognize text in various settings, I’m comparing its result with open source OCR’s and it produces quite inaccurate results, I’ve attached the document image,
Aspose OCR result sample:
MWlachine-Learninz Models for Sales Tim
i papEr Is an extended versiun ol conferere paper: Lohdan Pavlyrhenko. USig Stackind ApProachès
lhe maihgoal of thls paper is fo qOhsider main approachèS and tcase Stludlies or usig mâchine learhin;
lechniqjues, Wwe can improve the performance olt predictive modèls lor sales time series torecasl
Dales prediction is an important part ol modern business üunteligence I1-3I. It can be a comple?
pefoblèrmh, eSpetcially in the câe ol lack ol
************* Trial Licenses *************
Open Source OCR result sample:
Machine-Learning Models for Sales Time
Series Forecasting *
Bohdan M. Pavlyshenko 1?
‘This paper is an extended version of conference paper: Bohdan Pavlyshenko. Using Stacking Approaches
for Machine Learning Models. In Proceedings of the 2018 IEEE Second International Conference on Data
Stream Mining & Processing (DSMP), Lviv, Ukraine, 21-25 August 2018.
Received: 3 November 2018; Accepted: 14 January 2019; Published: 18 January 2019 updates
Abstract: In this paper, we study the usage of machine-learning models for sales predictive analytics.
‘The main goal of this paper is to consider main approaches and case studies of using machine learning,
for sales forecasting, The effect of machine-learning generalization has been considered. This effect
can be used to make sales predictions when there is a small amount of historical data for specific
sales time series in the case when a new product or store is launched. A stacking approach for
building regression ensemble of single models has been studied. The results show that using stacking,
techniques, we can improve the performance of predictive models for sales time series forecasting,
Keywords: machine learning; stacking; forecasting; regression; sales; time series
data-04-00015-v21.Png (86.8 KB)
can you provide some information regarding this issue.