#加载数据 defload_exdata(filename):data=[]withopen(filename,'r')asf:forlineinf.readlines():line=line.split(',')current=[int(item)foriteminline]#5.5277,9.1302data.append(current)returndata data=load_exdata('ex1data2.txt');data=np.array(data,np.int64)x=data[:,(0,1)].reshape((-1,...
data.append(current) returndata data=load_exdata('ex1data2.txt'); data=np.array(data,np.int64) x=data[:,(0,1)].reshape((-1,2)) y=data[:,2].reshape((-1,1)) m=y.shape[0] # Print out some data points print('First 10 examples from the dataset: \n') print(' x = ',x...
data.append(current) returndata data=load_exdata('ex1data2.txt'); data=np.array(data,np.int64) x=data[:,(0,1)].reshape((-1,2)) y=data[:,2].reshape((-1,1)) m=y.shape[0] # Print out some data points print('First 10 examples from the dataset: \n') print(' x = ',x...
The Return statement is used to exit the function and return the program to the location of the function call to continue execution. A Return statement can return the result of multiple function operations to the variable on which the function was called. Without return, the function does not ...
6. Python Function Return Value Python allows function to return multiple values. def prime_numbers(x): l=[] for i in range(x+1): if checkPrime(i): l.append(i) return len(l), l no_of_primes, primes_list = prime_numbers(100) ...
Passing multiple variables as arguments separating them by commas To print multiple variables using theprint()function, we need to provide the variable names as arguments separated by the commas. Note:print()function prints space after the value of each variable, space is the default value ofsep...
多变量线性回归(Linear Regression with multiple variables) (1) 多维特征 & 多变量梯度下降 概念: 多维特征,顾名思义就是指有多个特征值或者多个变量组成的。与单变量不同的就是多了一些特征量而已。因此之前所述的数学公式只需要修改一下,即: 多变量的假设函数: ...
Decorators in Python are syntax to allow one function to modify another function at runtime. import time, functools def metric(fn): @functools.wraps(fn) def wrapper(*args, **kw): start_time = time.time() r = fn(*args, **kw) ...
在各种代价函数中,最常用的是平方误差代价函数 Squared error cost function。 """ theta是一个n维列向量 X是一个m行n列的矩阵(单变量情况下,是两列(包含一个变量和theta_0)) y是一个m行1列的矩阵(m维的列向量) """ def h(X,theta): # 计算线性假设函数h(x) ...
defvery_important_function(template:str, *variables, file: os.PathLike, engine:str, header:bool=True, debug:bool=False):"""Applies `variables` to the `template` and writes to `file`."""withopen(file,'w')asf: ... 和我们前面未进行格式化的代码例子类似,不过这里由于very_important_function函...