PLS算法python实现

Sure, I can help with that! The PLS algorithm is a regression method. Here is an example Python implementation:

from numpy import *
from numpy.linalg import norm

def pls(X, y, ncomp):
    # Apply PLS algorithm with ncomp number of components
    n, p = X.shape
    t = zeros((n, ncomp))
    w = zeros((p, ncomp))
    b = zeros(ncomp)
    u = y.copy()
    for i in range(ncomp):
        w[:,i] = dot(X.T, u) / norm(dot(X.T, u))
        t[:,i] = dot(X, w[:,i])
        b[i] = dot(t[:,i], u) / dot(t[:,i], t[:,i])
        u -= b[i] * t[:,i]
    y_pred = dot(t, b)
    return y_pred

You can call this function with your X and y data, and specify the number of components you want to use. Let me know if you have any more questions!