File size: 1,344 Bytes
c080ddb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 |
# set path
import glob, os, sys;
sys.path.append('../utils')
#import needed libraries
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import streamlit as st
from utils.conditional_classifier import load_conditionalClassifier, conditional_classification
import logging
logger = logging.getLogger(__name__)
from utils.config import get_classifier_params
from io import BytesIO
import xlsxwriter
import plotly.express as px
# Declare all the necessary variables
classifier_identifier = 'conditional'
params = get_classifier_params(classifier_identifier)
def app():
### Main app code ###
with st.container():
if 'key1' in st.session_state:
df = st.session_state.key1
# Load the classifier model
classifier = load_conditionalClassifier(classifier_name=params['model_name'])
st.session_state['{}_classifier'.format(classifier_identifier)] = classifier
if sum(df['Target Label'] == 'TARGET') > 100:
warning_msg = ": This might take sometime, please sit back and relax."
else:
warning_msg = ""
df = conditional_classification(haystack_doc=df,
threshold= params['threshold'])
st.session_state.key1 = df |