NeuralNetworks project RT(RNN + LSTM) solution needed. Write a function to detecte lead-lag relationship between two timeseries (vector<double>)
$750-1500 USD
Płatność przy odbiorze
Hello,
I need a function written in c++ (qt, ubuntu) that takes input 2 vector<double> and outputs which one of the 2 vectors is behind (lagging) and by how much. The solution has to implement reinforcement-learning (RT) techniques (Q-Learning?) on a RNN (recurent neural net) using your choice library (propose, explain why the choice). The NeuralNetwork will be "default" trained on some data i will provide in a file and the function you will write is expected to keep on training itself and get better at finding by how much the lagging vector is behind, as more data arrives. The code has to run fast, c++ ONLY is expected.
possible declaration:
struct Out {
string Who;
double HowMuch;
};
Out LeadLag(const vector<double>& A, const vector<double>& B) {}
A and B vectors contain the same amount of data all the time and the values are correlated and cointegrated but can move in totally different ranges.
Example1 (picture example):
A = { 1000, 1001, 1001, 1001, 998}
B= { 999, 999, 1002 , 997, 997}
Example2, totally different ranges but same relative movement:
A = { 1000, 1001, 1001, 1001, 998}
B = {0.05, 0.05, 0.08, 0.03, 0.03}
More about the functionality: The vectors will be continously updated when new data arrives, both at the same time. (A.push_back(new_value), B.push_back(new_value) outside the function. Then, the function, will be called every time for each update of the data.
The function has to return who of the two vectors is behind (A or B) and by how much X.
For example1 (picture). At T1, the function has to return({"B",1}). since B is latent by 1. At T3 function will return({"A",3}) since A is latent by 3.
*Please bid only if you have good experience with neural netowrks and c++.
*Do not bid until you've read the requirement fully and you think you can do this.
*Payment will be done 100% only at the end of the project.A Partial solution is not a solution. Code has to run and detect the pattern with at least 80% accuracy.
p.s You can propose other solutions that are not about neural netowrks. In the end the main problem is to detect who lags and by how much out of the two vectors.
Numer ID Projektu: #18383282
O projekcie
Przyznany użytkownikowi:
Like you've described I would also recommend basic RNN neural network if vectors are low dimensions, else I would suggest using LSTM network. But mostly your task requires preprocessing part where you need to compare b Więcej
12 freelancerów złożyło ofertę za $1240 w tym projekcie
Hi, Dear Employer! I am really interested in your project. I have enough experience in Python, C/C++, C#, java programming. Especially, I am an expert in machine learning. I am 100% sure I can satisfy your require Więcej
hello,how are you. i read your bid carefully. i am c/c++, qt expert and have full experience for 10 years. c/c++, qt is my top skill and i can build your project fully by using that skills. i can provide most qualit Więcej
Hi there, I have checked the details I have rich experienced with C++ Programming, Machine Learning, Neural Networks, Tensorflow. Please initiate chat so we can discuss this job.
hello, I have read the details provided and i am confident i can produce..please contact me to discuss more on the project deadline and some other few things
Hi,dear. I am very interested in your project - 'NeuralNetworks project RT(RNN + LSTM) solution needed. Write a function to detecte lead-lag relationship between two timeseries (vector<double>)'. I've already done this Więcej
We are a company based out of Gurugram,India Working on some Core AI and Blockchain Technologies. Some of our core services offered:- 1. Text to Speech/Speech to Text 2. Blockchain/Smart Contracts 3. Face Recognition/Q Więcej
