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Algorithm required in R

$80-240 HKD

Completato
Pubblicato più di 5 anni fa

$80-240 HKD

Pagato al completamento
About Data: My acquired data is composed to a number of traces (T) and No. of samples per Trace (S) and it makes a matrix of dimension TxS. ‘T’ in our case is 10,000 traces and ‘S’ represents the number of approximately 25,000 samples per trace. A perturbation occurs at a certain location along the length ‘S’, and all the traces represent this perturbation, to be different from the rest of the samples. In my case this perturbed location ranges from 21,940 to 21,960 (specified as DV_min and DV_max in M-File). I have applied the ‘Corr’ algorithm to show this perturbation. The Raw data also show the perturbation location to be different from rest of the samples if viewed closely. The M-file is attached to show a plot representing this perturbed location. Two CSV files (Vector form and Matrix form) from processed data have been generated for the expert to load the lighter version of data to R-program. The expert may use any of these 02 CSV files in R-program, whatever feasible for him/her, to differentiate perturbed region from that of non-perturbed one. Expert Task: The expert is required to apply some algorithm in R that should distinguish the data of perturbed region from that of non-perturbed region. He/She may find any specific pattern in perturbed region that is different from that of non-perturbed region. He/She can notice that by increasing the R_Samples value (~150-200), the perturbed region should be seen quite differentiable than that of non-perturbed region. In the current situation, by increasing the value of R_Samples, the perturbed region can easily be differentiated from non-perturbed region by taking a simple mean of parts of data, but this logic is not good if value of R_Samples is too low. The algorithm should be so powerful that the perturbed region should be differentiated from non-perturbed region for small values of R_Samples (R_Samples < 40). The algorithm should be valid for all the Data-Files, the links of which are provided here-with. Data Files are attached in following links: D_SIN_100H_02V: ([login to view URL] ) D_Sq_100H_02V: ([login to view URL] ) D_SIN_100H_1V: ([login to view URL] ) D_SIN_100H_r10V: ([login to view URL] ) D_SIN_100H_01V: ([login to view URL] )
Rif. progetto: 17343847

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Attivo 6 anni fa

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I am [login to view URL] from IIT Delhi. I have done specialisations in machine learning and deep learning. I have worked on Predictive Analytics,data mining, Object Detection and Object Recognition problems. I have 6 years of working experience in R. Some of the work that I have done in R includes - 1) Time series analysis- ARIMA, MDFA 2) Machine Learning projects - RF, NN, GBM etc 3) Data Analytics Projects using integration with SQL 4) Packages used - RMD, Shiny, rvest etc
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Hi I am a very experienced statistician, programmer and academic writer. I have completed several PhD level thesis projects involving advanced statistical analysis of data. I have worked with data from several companies and have done projects involving high level quantitative analysis and data interpretation skills to study the trends, time behaviour and compare the variables in the data. I can do advanced level analysis in SPSS, R, PYTHON, WEKA, TABLEAU and EXCEL tools like machine learning, hypothesis testing, forecasting, T-test, ANOVA etc. Looking forward to discussion, Best Regards, Suyash
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Industrial engineer and project engineering Phd. More than 8 years experiences with MATLAB/ANSYS/SIMULINK/R/SPSS/EXCEL/SOLIDWORKS....I can solve all your problem in the field of : mathematics, electrical engineering, mechanical engineering,control and automation, data analysis, strengh of materials, physics, fluid mechanical, computational fluid dynamics, system modeling, heat transfert, hydraulics, statistics, linear programming,finite element analysis. free to colaborate with you (long term) please see my portfolio Best regards
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Bandiera: HONG KONG
Kowloon, Hong Kong
5,0
3
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Membro dal nov 1, 2016

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