“Python Machine Learning” Ответ

машинное обучение питон

import pandas as pd
from sklearn.tree import DecisionTreeClassifier

hashdata = pd.read_csv("filename.csv")
X = hashdata.drop(columns=["output_column_name"])
y = hashdata.drop(columns=["input_column_name"])
model=DecisionTreeClassifier()
model.fit(X,y)
predictions=model.predict([[input]])
print(predictions)

Blue Bee

Python Machine Learning

# Create Decision Tree classifer object
clf = DecisionTreeClassifier(criterion="entropy", max_depth=3)

# Train Decision Tree Classifer
clf = clf.fit(X_train,y_train)

#Predict the response for test dataset
y_pred = clf.predict(X_test)

# Model Accuracy, how often is the classifier correct?
print("Accuracy:",metrics.accuracy_score(y_test, y_pred))

Ruben Visser

Смотреть популярные ответы по языку

Смотреть другие языки программирования

Shell/Bash

C++

CSS

HTML

Java

JavaScript

Objective-C

PHP

Python

Sql

Swift

Ruby

TypeScript

Kotlin

Assembly

VBA

Scala

Rust

Dart

Elixir

Clojure

Haskell

Matlab

Erlang

Cobol

Fortran

Scheme

Perl

Groovy

Lua

Julia

Delphi

Abap

Lisp

Prolog

Pascal

ActionScript

Basic

Solidity

PowerShell

GDScript

Excel