Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 9705273
- CO2 Emissions (in grams): 0.0006300767567816624
Validation Metrics
- Loss: 0.15987505325856152
- Accuracy: 0.9
- Macro F1: 0.899749373433584
- Micro F1: 0.9
- Weighted F1: 0.8997493734335841
- Macro Precision: 0.9023569023569024
- Micro Precision: 0.9
- Weighted Precision: 0.9023569023569025
- Macro Recall: 0.9
- Micro Recall: 0.9
- Weighted Recall: 0.9
Usage
import json
import joblib
import pandas as pd
model = joblib.load('model.joblib')
config = json.load(open('config.json'))
features = config['features']
# data = pd.read_csv("data.csv")
data = data[features]
data.columns = ["feat_" + str(col) for col in data.columns]
predictions = model.predict(data) # or model.predict_proba(data)
前往AI网址导航
收录说明：
1、本网页并非 abhishek/autotrain-iris-logistic-regression 官网网址页面，此页面内容编录于互联网，只作展示之用；2、如果有与 abhishek/autotrain-iris-logistic-regression 相关业务事宜，请访问其网站并获取联系方式；3、本站与 abhishek/autotrain-iris-logistic-regression 无任何关系，对于 abhishek/autotrain-iris-logistic-regression 网站中的信息，请用户谨慎辨识其真伪。4、本站收录 abhishek/autotrain-iris-logistic-regression 时，此站内容访问正常，如遇跳转非法网站，有可能此网站被非法入侵或者已更换新网址，导致旧网址被非法使用,5、如果你是网站站长或者负责人，不想被收录请邮件删除：i-hu#Foxmail.com （#换@）
