I have an excel file that contains details related to determining the quality of a wine and I want to implement the linear model concept using the function sklearn.linear_model.SGDClassifier(SVM => Hinge loss) and (Logarithmic regression =>log loss) using python. I learned the basics about these function through the scikit learn website and I am not able to implement the model using excel file. I am very new to python and machine learning and I finding it hard to implement the model. I opened the excel file in python and tried to take two columns [randomly] from the file and use that as an input to call the fit function available in the model. But, I got an error stating Unknown label type: array. I tried a couple of other methods too, but, nothing worked. Can someone guide me with the implementation process?
from xlrd import open_workbook from sklearn import linear_model i = 0 fa =  ph =  book = open_workbook('F:/BIG DATA/winequality.xlsx') sheet = book.sheet_by_name('Sheet1') num_rows = sheet.nrows - 1 num_cols = sheet.ncols - 1 curr_row = 0 while curr_row <num_rows: curr_row += 1 cell_val = sheet.cell_value(curr_row,0) cell_val1 = sheet.cell_value(curr_row,10) fa.append([float(cell_val),float(cell_val1)]) cell_val2 = sheet.cell_value(curr_row,8) ph.append(float(cell_val2)) model = linear_model.SGDClassifier() print(model.fit(fa,ph))
The error message screenshot: