问题描述
使用 ktrain 模型无法预测前端流光,请提供有关如何为预测功能提供输入的建议。
基本上,我想了解如何为我保存的 ktrain 回归模型提供输入,以便我可以将其合并到流线型 Web 应用程序按钮中。
我尝试将数组、列表和数据框作为参数放入 .predict 函数中,但似乎仍然缺少一些东西。当点击预测按钮时出现值错误。
import streamlit as st
from PIL import Image
import pandas as pd
from tensorflow import keras
model = keras.models.load_model("predictor.h5")
st.write("This is an application to calculate Employee Mental Fatigue score")
image = Image.open("IMG_2605.jpeg")
st.image(image,use_column_width=True)
WFH_Setup_Available = st.text_input("is work from home enabled for you?")
Designation =st.text_input("what is your designation?")
Average_hours_worked_per_day = st.text_input("how many hours you work on an average per day?")
Employee_satisfaction_score = st.text_input("Please enter your satisfaction score on scale of 10")
data = ['WFH_Setup_Available','Designation','Average_hours_worked_per_day','Employee_satisfaction_score']
def mental_fatigue_score(WFH_Setup_Available,Designation,Average_hours_worked_per_day,Employee_satisfaction_score):
prediction = model.predict([[WFH_Setup_Available,Employee_satisfaction_score]])
print(prediction)
return prediction
if st.button("Predict"):
result= mental_fatigue_score(WFH_Setup_Available,Employee_satisfaction_score)
st.success('The output is {}'.format(result))
请建议如何为流线型 Web 应用程序的 .predict 函数提供输入。 我已经使用 ktrain 回归器训练了预测器。
解决方法
自己解决了,将ktrain模型另存为
predictor.save('predictor')
predictor = ktrain.load_predictor('predictor')
当我保存为预测器时,它会创建一个文件夹,其中有一个 tf_mode.h5 和 tf_model.preproc。
这比我预期的要容易。
进一步的训练输入应该是像下面这样的数据框-
data = {'WFH_Setup_Available':WFH_Setup_Available,'Designation':Designation,'Company_Type':Company_Type,'Average_hours_worked_per_day': Average_hours_worked_per_day,'Employee_satisfaction_score': Employee_satisfaction_score}
data = pd.DataFrame([data])