How to use regression in Avalanche

[raul-parada]

I would like to adapt Avalanche in my code. The dataset is composed of Cartesian coordinates in which X and y are the same. I've solved the fact of using a 2D in the y with this simple solution.

X = raw[:-1]
y = raw[1:]

Mention these two lines above allow that both latitude and longitude can be used as data and label. Since coordinates are a unique pair of lat/lon, I cannot apply a label to each cartesian coordinates

This is the code:

#!pip install haversine
from sklearn.linear_model import SGDRegressor
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_squared_error
import haversine as hs
from haversine import Unit
num=10

i=1

while((i*num+1)<len(10)):
  raw= dat[0:(i*num)]
  X = raw[:-1]
  y = raw[1:]
  regressor = SGDRegressor(max_iter=1000, tol=1e-3, random_state=42)
  #regressor = LinearRegression()
  regressor.partial_fit(X, y)

  pred=regressor.predict([raw[(i*num)-1]])
  hs.haversine(( pred[0,0] , pred[0,1] ),( dat[(i*num),0] , dat[(i*num),1] ), unit=Unit.METERS)
  i=i+1

The piece of data can be obtained from here:

import pandas as pd
import io

content = """latitude(m) longitude(m)
41.392245 2.162762
41.392261 2.162783
41.392292 2.162825
41.392340 2.162888
41.392369 2.162943
41.392405 2.163008
41.392454 2.163093
41.392520 2.163186
41.392600 2.163296
41.392687 2.163417"""

# Create a file-like object from the content string
file_obj = io.StringIO(content)

# Load the content into a DataFrame
raw = pd.read_csv(file_obj, delimiter='\t' or ' ')

I've already installed Avalanche and imported the useful libraries. However, I don't know how to do regression using this simple code into Avalanche. Please, could help me on this? Thank you.