Example of training an HDBSCAN model using the hdbscan Python package in Scikit-learn contrib:
from sklearn import datasets
from hdbscan import HDBSCAN
X = datasets.make_moons(n_samples=50, noise=0.05)
model = HDBSCAN(min_samples=5)
With Audio and Screen Sharing Enabled
IMPORTANT NOTE :
1. The Screen Sharing works when you use Xorg instead of Wayland.
2. In my test, I disabled SELinux but maybe it works even if SElinux is permissive.
3. This was tested and worked on the DELL VOSTRO 3560 but does not work on DELL PRECISION 7510
echo "Downloading gcc source files..." | |
curl https://ftp.gnu.org/gnu/gcc/gcc-5.4.0/gcc-5.4.0.tar.bz2 -O | |
echo "extracting files..." | |
tar xvfj gcc-5.4.0.tar.bz2 | |
echo "Installing dependencies..." | |
yum install gmp-devel mpfr-devel libmpc-devel -y | |
echo "Configure and install..." |
import numpy as np | |
import pylab as pl | |
from numpy import fft | |
def fourierExtrapolation(x, n_predict): | |
n = x.size | |
n_harm = 10 # number of harmonics in model | |
t = np.arange(0, n) | |
p = np.polyfit(t, x, 1) # find linear trend in x | |
x_notrend = x - p[0] * t # detrended x |