Skip to content

Fix #717: Corrected PCA sign flip and updated test compatibility for … #1158

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
mariam851 wants to merge 2 commits into
base: master
Choose a base branch
from
Open

Fix #717: Corrected PCA sign flip and updated test compatibility for … #1158

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
7e24ddd
Fix #717: Corrected PCA sign flip and updated test compatibility for …
mariam851 Jan 18, 2026
d1eff3a
Merge branch 'master' into fix-pca-sign-717
rasbt Jan 24, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
3 changes: 0 additions & 3 deletions docs/ipynb2markdown.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -9,13 +9,10 @@

import glob
import os
import shutil
import subprocess

import markdown
from markdown.extensions import Extension
from markdown.treeprocessors import Treeprocessor
from nbconvert.exporters import MarkdownExporter


class ImgExtractor(Treeprocessor):
Expand Down
6 changes: 3 additions & 3 deletions docs/make_api.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -416,13 +416,13 @@ def summarize_methdods_and_functions(
"-o1",
"--output_module_api",
default="../docs/sources/api_modules",
help=("Target directory for the module-level" " API Markdown files"),
help=("Target directory for the module-level API Markdown files"),
)
parser.add_argument(
"-o2",
"--output_subpackage_api",
default="../docs/sources/api_subpackages",
help=("Target directory for the" " subpackage-level API Markdown files"),
help=("Target directory for the subpackage-level API Markdown files"),
)
parser.add_argument(
"-c", "--clean", action="store_true", help="Remove previous API files"
Expand Down Expand Up @@ -459,5 +459,5 @@ def summarize_methdods_and_functions(
out_dir=args.output_subpackage_api,
printlog=not (args.silent),
clean=args.clean,
str_above_header=("mlxtend" " version: %s \n" % (package.__version__)),
str_above_header=("mlxtend version: %s \n" % (package.__version__)),
)
103 changes: 53 additions & 50 deletions docs/sources/user_guide/classifier/Adaline.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -178,22 +178,19 @@
"# Loading Data\n",
"\n",
"X, y = iris_data()\n",
"X = X[:, [0, 3]] # sepal length and petal width\n",
"X = X[0:100] # class 0 and class 1\n",
"y = y[0:100] # class 0 and class 1\n",
"X = X[:, [0, 3]] # sepal length and petal width\n",
"X = X[0:100] # class 0 and class 1\n",
"y = y[0:100] # class 0 and class 1\n",
"\n",
"# standardize\n",
"X[:,0] = (X[:,0] - X[:,0].mean()) / X[:,0].std()\n",
"X[:,1] = (X[:,1] - X[:,1].mean()) / X[:,1].std()\n",
"X[:, 0] = (X[:, 0] - X[:, 0].mean()) / X[:, 0].std()\n",
"X[:, 1] = (X[:, 1] - X[:, 1].mean()) / X[:, 1].std()\n",
"\n",
"\n",
"ada = Adaline(epochs=30, \n",
" eta=0.01, \n",
" minibatches=None, \n",
" random_seed=1)\n",
"ada = Adaline(epochs=30, eta=0.01, minibatches=None, random_seed=1)\n",
"ada.fit(X, y)\n",
"plot_decision_regions(X, y, clf=ada)\n",
"plt.title('Adaline - Closed Form')\n",
"plt.title(\"Adaline - Closed Form\")\n",
"\n",
"plt.show()"
]
Expand Down Expand Up @@ -261,29 +258,31 @@
"# Loading Data\n",
"\n",
"X, y = iris_data()\n",
"X = X[:, [0, 3]] # sepal length and petal width\n",
"X = X[0:100] # class 0 and class 1\n",
"y = y[0:100] # class 0 and class 1\n",
"X = X[:, [0, 3]] # sepal length and petal width\n",
"X = X[0:100] # class 0 and class 1\n",
"y = y[0:100] # class 0 and class 1\n",
"\n",
"# standardize\n",
"X[:,0] = (X[:,0] - X[:,0].mean()) / X[:,0].std()\n",
"X[:,1] = (X[:,1] - X[:,1].mean()) / X[:,1].std()\n",
"X[:, 0] = (X[:, 0] - X[:, 0].mean()) / X[:, 0].std()\n",
"X[:, 1] = (X[:, 1] - X[:, 1].mean()) / X[:, 1].std()\n",
"\n",
"\n",
"ada = Adaline(epochs=30, \n",
" eta=0.01, \n",
" minibatches=1, # for Gradient Descent Learning\n",
" random_seed=1,\n",
" print_progress=3)\n",
"ada = Adaline(\n",
" epochs=30,\n",
" eta=0.01,\n",
" minibatches=1, # for Gradient Descent Learning\n",
" random_seed=1,\n",
" print_progress=3,\n",
")\n",
"\n",
"ada.fit(X, y)\n",
"plot_decision_regions(X, y, clf=ada)\n",
"plt.title('Adaline - Gradient Descent')\n",
"plt.title(\"Adaline - Gradient Descent\")\n",
"plt.show()\n",
"\n",
"plt.plot(range(len(ada.cost_)), ada.cost_)\n",
"plt.xlabel('Iterations')\n",
"plt.ylabel('Cost')"
"plt.xlabel(\"Iterations\")\n",
"plt.ylabel(\"Cost\")"
]
},
{
Expand Down Expand Up @@ -339,29 +338,31 @@
"# Loading Data\n",
"\n",
"X, y = iris_data()\n",
"X = X[:, [0, 3]] # sepal length and petal width\n",
"X = X[0:100] # class 0 and class 1\n",
"y = y[0:100] # class 0 and class 1\n",
"X = X[:, [0, 3]] # sepal length and petal width\n",
"X = X[0:100] # class 0 and class 1\n",
"y = y[0:100] # class 0 and class 1\n",
"\n",
"# standardize\n",
"X[:,0] = (X[:,0] - X[:,0].mean()) / X[:,0].std()\n",
"X[:,1] = (X[:,1] - X[:,1].mean()) / X[:,1].std()\n",
"X[:, 0] = (X[:, 0] - X[:, 0].mean()) / X[:, 0].std()\n",
"X[:, 1] = (X[:, 1] - X[:, 1].mean()) / X[:, 1].std()\n",
"\n",
"\n",
"ada = Adaline(epochs=15, \n",
" eta=0.02, \n",
" minibatches=len(y), # for SGD learning \n",
" random_seed=1,\n",
" print_progress=3)\n",
"ada = Adaline(\n",
" epochs=15,\n",
" eta=0.02,\n",
" minibatches=len(y), # for SGD learning\n",
" random_seed=1,\n",
" print_progress=3,\n",
")\n",
"\n",
"ada.fit(X, y)\n",
"plot_decision_regions(X, y, clf=ada)\n",
"plt.title('Adaline - Stochastic Gradient Descent')\n",
"plt.title(\"Adaline - Stochastic Gradient Descent\")\n",
"plt.show()\n",
"\n",
"plt.plot(range(len(ada.cost_)), ada.cost_)\n",
"plt.xlabel('Iterations')\n",
"plt.ylabel('Cost')\n",
"plt.xlabel(\"Iterations\")\n",
"plt.ylabel(\"Cost\")\n",
"plt.show()"
]
},
Expand Down Expand Up @@ -418,29 +419,31 @@
"# Loading Data\n",
"\n",
"X, y = iris_data()\n",
"X = X[:, [0, 3]] # sepal length and petal width\n",
"X = X[0:100] # class 0 and class 1\n",
"y = y[0:100] # class 0 and class 1\n",
"X = X[:, [0, 3]] # sepal length and petal width\n",
"X = X[0:100] # class 0 and class 1\n",
"y = y[0:100] # class 0 and class 1\n",
"\n",
"# standardize\n",
"X[:,0] = (X[:,0] - X[:,0].mean()) / X[:,0].std()\n",
"X[:,1] = (X[:,1] - X[:,1].mean()) / X[:,1].std()\n",
"X[:, 0] = (X[:, 0] - X[:, 0].mean()) / X[:, 0].std()\n",
"X[:, 1] = (X[:, 1] - X[:, 1].mean()) / X[:, 1].std()\n",
"\n",
"\n",
"ada = Adaline(epochs=15, \n",
" eta=0.02, \n",
" minibatches=5, # for SGD learning w. minibatch size 20\n",
" random_seed=1,\n",
" print_progress=3)\n",
"ada = Adaline(\n",
" epochs=15,\n",
" eta=0.02,\n",
" minibatches=5, # for SGD learning w. minibatch size 20\n",
" random_seed=1,\n",
" print_progress=3,\n",
")\n",
"\n",
"ada.fit(X, y)\n",
"plot_decision_regions(X, y, clf=ada)\n",
"plt.title('Adaline - Stochastic Gradient Descent w. Minibatches')\n",
"plt.title(\"Adaline - Stochastic Gradient Descent w. Minibatches\")\n",
"plt.show()\n",
"\n",
"plt.plot(range(len(ada.cost_)), ada.cost_)\n",
"plt.xlabel('Iterations')\n",
"plt.ylabel('Cost')\n",
"plt.xlabel(\"Iterations\")\n",
"plt.ylabel(\"Cost\")\n",
"plt.show()"
]
},
Expand Down Expand Up @@ -641,7 +644,7 @@
}
],
"source": [
"with open('../../api_modules/mlxtend.classifier/Adaline.md', 'r') as f:\n",
"with open(\"../../api_modules/mlxtend.classifier/Adaline.md\", \"r\") as f:\n",
" print(f.read())"
]
}
Expand Down
Loading
Loading