rish2911 / MPC-Control-Output-training-using-Lidar-and-Robot-Pose-Data

###How to run code

#Dependencies XGBoost Sklearn Python3

##LIBRARIES ####Sklearn pip3 install -U scikit-learn

###In order to check your installation you can use python -m pip3 show scikit-learn # to see which version and where scikit-learn is installed python -m pip3 freeze # to see all packages installed in the active virtualenv python -c "import sklearn; sklearn.show_versions()"

####XGBoost library pip3 install xgboost

###Data Files

1. Copy the folder named with code in any directory
2. In the codes folder make a folder with name "Input_data" or download the data from this drive (link below)
3. Inside Input_data make folders with names"training" and "testing" (skip if downloaded above)
4. Copy the csv files in respective folders (skip if downloaded above)

###Running the code Check if the available scripts are (data_import.py, main.py, NeuralNet.py, pipeline.py, regression.py, SVM.py, utils.py, xg_boost.py)

1. Open the code directory in VSCode and run "main.py" script or execute "python3 path\code\main.py"
2. Select the model you want to run

In case of problem contact me at: [e-mail]

Download input data here: https://drive.google.com/drive/folders/1xyV-NAnSLSqlP6iQGp75n7eEHA-t-igw?usp=share_link