frenzy2106

'''
# Baseline script by Supreet Manyam (Ziron)

'''

import pandas as pd
import numpy as np
import gc

train = pd.read_csv("data/train.csv", 

frenzy2106

import numpy as np
import pandas as pd
from sklearn.metrics import f1_score
from copy import deepcopy

from collections import namedtuple

# Evaluation metric for Innoplexus NER Challenge

def collect_named_entities(tokens): # Helper Function for score calculation

frenzy2106

def apk(actual, predicted, k=3):
    """
    Computes the average precision at k.
    This function computes the average prescision at k between two lists of
    items.
    Parameters
    ----------
    actual : list
             A list of elements that are to be predicted (order doesn't matter)
    predicted : list