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1 from sklearn.datasets import load_boston 2 from sklearn.model_selection import train_test_split 3 boston=load_boston() 4 X,y=boston.data,boston.targ 阅读全文
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1 import numpy as np 2 import matplotlib.pyplot as plt 3 from sklearn import svm 4 from sklearn.datasets import make_blobs 5 X,y=make_blobs(n_samples= 阅读全文
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1 from sklearn import tree,datasets 2 from sklearn.model_selection import train_test_split 3 wine=datasets.load_wine() 4 X,y=wine.data[:,:2],wine.targ 阅读全文
摘要:
1 from sklearn import tree,datasets 2 from sklearn.model_selection import train_test_split 3 wine=datasets.load_wine() 4 X,y=wine.data[:,:2],wine.targ 阅读全文
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毕生所学。 1 const int N = 2e5 + 10; 2 #define lson rt << 1 // == rt * 2 左儿子 3 #define rson rt << 1 | 1 // == rt * 2 + 1 右儿子 4 #define int_mid int mid = tr 阅读全文
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入门级数据结构算法。复习一下,分别手写一个。 线段树版本(过了CF上的https://codeforces.com/contest/1291/problem/D): 1 #include<bits/stdc++.h> 2 #define f(i,a,b) for(int i=a;i<=b;i++) 阅读全文
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原理很简单,利用差分知识做的,只能单点查询,在性能上优于线段树,但没有区间查询功能。 1 #include<bits/stdc++.h> 2 #define f(i,a,b) for(int i=a;i<=b;i++) 3 using namespace std; 4 5 const int N=5 阅读全文
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1 from sklearn.datasets import load_wine 2 from sklearn.preprocessing import StandardScaler 3 wine=load_wine() 4 X,y=wine.data,wine.target 5 scaler=St 阅读全文
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简单的字符串算法。出一个纯原创板子吧。 不要忘记字典树和哈希的联系。 HDU1251,计算相同前缀的数目。 1 #include<bits/stdc++.h> 2 #define scan(i) scanf("%d",&i) 3 #define pf printf 4 #define ll long 阅读全文
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1 from sklearn.datasets import load_wine 2 from sklearn.model_selection import train_test_split 3 import numpy as np 4 wine_dataset=load_wine() 5 X,y= 阅读全文