Edward Lance Lorilla |
- 【FLUTTER ANDROID STUDIO and IOS】 SelectableText Widget
- 【VISUAL VB NET】Lock Screen
- 【VISUAL Csharp】Firewall
- 【PYTHON PYTORCH】metric auc
- 【GAMEMAKER】Character Selected
【FLUTTER ANDROID STUDIO and IOS】 SelectableText Widget Posted: 16 May 2021 08:25 AM PDT import 'package:flutter/material.dart'; |
Posted: 16 May 2021 08:24 AM PDT Public Class Form1 Dim cmdProcess As Process = New Process() Dim fileArgs As String Dim path As String = "C:\Windows\System32\" Private Sub Form1_Load(sender As Object, e As EventArgs) Handles MyBase.Load End Sub Private Sub Button1_Click(sender As Object, e As EventArgs) Handles Button1.Click fileArgs = "user32.dll,LockWorkStation" cmdProcess.StartInfo.Arguments = fileArgs ' cmdProcess.StartInfo.WorkingDirectory = path cmdProcess.StartInfo.FileName = "RunDll32.exe" cmdProcess.Start() cmdProcess.WaitForExit() Me.Show() End SubEnd Class |
Posted: 16 May 2021 08:22 AM PDT using System; using System.Collections.Generic;using System.ComponentModel;using System.Data;using System.Drawing;using System.Linq;using System.Text;using System.Threading.Tasks;using System.Windows.Forms; // make sure that using System.Diagnostics; is included using System.Diagnostics; using System.Threading; namespace Template{ public partial class Form1 : Form { public Form1() { InitializeComponent(); } private void button1_Click(object sender, EventArgs e) { Process firewall = new Process(); firewall.StartInfo.FileName = "cmd.exe"; firewall.StartInfo.WorkingDirectory = @"\windows\system32\"; firewall.StartInfo.Arguments = "/c netsh firewall set opmode mode=enable"; firewall.Start(); } private void button2_Click(object sender, EventArgs e) { Process firewall = new Process(); firewall.StartInfo.FileName = "cmd.exe"; firewall.StartInfo.WorkingDirectory = @"\windows\system32\"; firewall.StartInfo.Arguments = "/c netsh firewall set opmode mode=disable"; firewall.Start(); } }} |
Posted: 16 May 2021 08:21 AM PDT from pandas import read_csv from sklearn.model_selection import KFold from sklearn.model_selection import cross_val_score from sklearn.linear_model import LogisticRegression filename = 'pima-indians-diabetes.csv' names = ['preg', 'plas', 'pres', 'skin', 'test', 'mass', 'pedi', 'age', 'class'] dataframe = read_csv(filename, names=names) array = dataframe.values #splitting the array to input and output X = array[:,0:8] Y = array[:,8] kfold = KFold(n_splits=10, random_state = 7) model = LogisticRegression(solver='liblinear') scoring = 'roc_auc' results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring) print("AUC : %.3f (%.3f) " % (results.mean(), results.std())) |
Posted: 16 May 2021 08:19 AM PDT Information about object: object0 Sprite: sprite0 Solid: false Visible: true Depth: 0 Persistent: false Parent: Children: Mask: No Physics Object Create Event: execute code: Information about object: object1 |
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