I want to execute SVM light and SVM rank,
so I need to process my data into the format of SVM light.
But I had a big problem....
My Python codes are below:
import pandas as pd
import numpy as np
from sklearn.datasets import dump_svmlight_file
self.df = pd.DataFrame()
self.df['patent_id'] = patent_id_list
self.df['Target'] = class_list
self.df['backward_citation'] = backward_citation_list
self.df['uspc_originality'] = uspc_originality_list
self.df['science_linkage'] = science_linkage_list
self.df['sim_bc_structure'] = sim_bc_structure_list
self.df['claim_num'] = claim_num_list
self.qid = dataset_list
X = self.df[np.setdiff1d(self.df.columns, ['patent_id','Target'])]
y = self.df.Target
dump_svmlight_file(X,y,'test.dat',zero_based=False, query_id=self.qid,multilabel=False)
The output file "test.dat" is look like this:
But the real data is look like this:
I got a wrong index....
Take first instance for example, the value of column 1 is 7, and the values of column 2~4 are zeros, the value of column 5 is 2....
So my expected result is look like this:
1 qid:1 1:7 5:2
but the column index of output file are totally wrong....
and unfortunately... I cannot figure out where is the problem occur....
I cannot fix this problem for a long time....
Thank you for help!!
