darden1

# -*- coding: utf-8 -*-
import sys
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap

def main():
    # ---アヤメデータの取得
    df = pd.read_csv("https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data", header=None)

darden1

# -*- encoding: utf-8 -*-
import numpy as np
import pandas as pd

df = pd.read_csv("https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data", header=None)
y = df.iloc[0:4, 4].values
y = np.where(y == "Iris-setosa", -1, 1)
X = df.iloc[0:4, [0, 2]].values

#---特徴行列

darden1

//+------------------------------------------------------------------+
//|                                                 DecisionTree.mq4 |
//|                        Copyright 2016, MetaQuotes Software Corp. |
//|                                             https://www.mql5.com |
//+------------------------------------------------------------------+
#property copyright "Copyright 2016, MetaQuotes Software Corp."
#property link      "https://www.mql5.com"
#property version   "1.00"
//#property strict

darden1

# -*- coding: utf-8 -*-
import poloniex
import time
import datetime
from sklearn import tree


def main():
    # --トレーニング用パラメータ
    theNumberOfTrainData=29   #トレーニングデータ数

darden1

# -*- coding: utf-8 -*-
import poloniex
import time
import datetime
from sklearn import tree
import matplotlib.pyplot as plt

def main():
    # --トレーニング用パラメータ
    theNumberOfTrainData=29   #トレーニングデータ数

darden1

# -*- coding: utf-8 -*-
import poloniex
import time
import datetime
from sklearn import tree
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import pickle

darden1

# -*- coding: utf-8 -*-
import sys
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap

def main():
    # ---アヤメデータの取得
    df = pd.read_csv("https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data", header=None)

darden1

# -*- coding: utf-8 -*-
import sys
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap

def main():
    # ---アヤメデータの取得
    df = pd.read_csv("https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data", header=None)

darden1

# -*- coding: utf-8 -*-
import sys
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap

def main():
    # ---アヤメデータの取得
    df = pd.read_csv("https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data", header=None)

darden1

# -*- coding: utf-8 -*-
import numpy as np

def main():
    m = 2  # 制約条件の個数
    n = 2  # 設計変数の個数
    x0 = np.matrix(np.zeros([n, 1]))  # x初期値(適当に0ベクトルで与える)

    print("-" * 80 + "\n■2つある制約条件のうちどちらも無効制約条件の場合")
    Q = np.matrix([[2, 0], [0, 2]])