* Be more specific about logistic regression solver in examples
* Use early stopped SGD (faster) and plot cross-validated error for best models
* Fix LR solver in /plot_voting_probas.pyexamples/ensemble/plot_voting_probas.py
* Fix LR solver & scale data in plot_digits_classification_exercise.py
* Use saga solver in plot_logistic_l1_l2_sparsity.py
* Use LBFGS solver in plot_iris_logistic.py
* Use LBFGS in plot_logistic.py
* Use SAGA solver for Logistic Regression Path example
* Use LBFGS solver in plot_classifier_chain_yeast.py
* Use LBFGS solver in plot_rbm_logistic_classification.py
* typo
* typo
* Bump up pandas dependency to 0.17.1
* Bump up examples minimal deps to match pandas 0.17.1
* Fix figure layout for plot_digits_pipe.py
* Version numbers are not decimal numbers
* Set multinomial, no scaling to keep example simple, fix formatting of example doc
* Missing plt.tight_layout() in plot_voting_probas.py
* Missing plt.tight_layout() in plot_logistic.py
* DOC examples with correct notebook style
* Modifications in examples/ to avoid unwanted notebook style
* Remove last notebook style example
* Space formatting to avoid notebook style
* Fix: Replace pylab with matplotlib.pyplot #6754
- one instance of 22 occurrences of pylab replaced with matplotlib.pyplot
- bench_glm.py now free of pylab references
- code executes properly
* Fix: Replace pylab with matplotlib.pyplot #6754
- one instance of 21 remaining occurrences of pylab replaced with
matplotlib.pyplot
- bench_glmnet.py now free of pylab references
- code does not execute for extraneous reason: ImportError: No module named
glmnet.elastic_net
* Fix: Replace pylab with matplotlib.pyplot #6754
- one instance of 19 occurrences of pylab replaced with matplotlib.pyplot
- bench_lasso.py now free of pylab references
- code executes properly
* Fix: Replace pylab with matplotlib.pyplot #6754
- one instance of 18 occurrences of pylab replaced with matplotlib.pyplot
- bench_plot_neighbors.py now free of pylab references
- code executes properly
* Fix: Replace pylab with matplotlib.pyplot #6754
- one instance of 17 occurrences of pylab replaced with matplotlib.pyplot
- bench_plot_omp_lars.py now free of pylab references
- code does not execute for extraneous reasons:
- File "bench_plot_omp_lars.py", line 111, in <module>
- ax = fig.add_subplot(1, 2, i)
- ValueError: num must be 1 <= num <= 2, not 0
- line 111 should probably be ax = fig.add_subplot(1, 2, i+1)
* Fix: Replace pylab with matplotlib.pyplot #6754
- bench_plot_parallel_pairwise.py now free of pylab references
- code executes properly
* Fix: Replace pylab with matplotlib.pyplot #6754
- bench_plot_ward.py now free of pylab references
- code executes properly
* Fix: Replace pylab with matplotlib.pyplot #6754
- bench_sgd_regression.py now free of pylab references
- code executes properly
* Fix: Replace pylab with matplotlib.pyplot #6754
- bench_tree.py now free of pylab references
- code executes properly
* refactor: Replace pl with plt
- replace instances of pl (as on import pylab as pl)
with plt (as in import matplotlib.pyplot as plt)
- bench_glm.py clean
* refactor: Replace pl with plt
- replace instances of pl (as on import pylab as pl)
with plt (as in import matplotlib.pyplot as plt)
- bench_glm.py clean of pl
- code does not execute for extraneous reasons
* refactor: Replace pl with plt
- replace instances of pl (as on import pylab as pl)
with plt (as in import matplotlib.pyplot as plt)
- bench_lasso.py clean of pl
- code executes properly
* refactor: Replace pl with plt
- replace instances of pl (as on import pylab as pl)
with plt (as in import matplotlib.pyplot as plt)
- bench_plot_neighbors.py clean of pl
- code executes properly
* refactor: Replace pl with plt
- replace instances of pl (as on import pylab as pl)
with plt (as in import matplotlib.pyplot as plt)
- bench_plot_omp_lars.py clean of pl
- code does not execute for extraneous reasons
* fix: Fix bug that prevented graphs from displaying
* refactor: Replace pl with plt
- replace instances of pl (as on import pylab as pl)
with plt (as in import matplotlib.pyplot as plt)
- bench_plot_parallel_pairwise.py clean of pl
- code executes properly
* refactor: Replace pl with plt
- replace instances of pl (as on import pylab as pl)
with plt (as in import matplotlib.pyplot as plt)
- bench_plot_ward.py clean of pl
- code executes properly
* refactor: Replace pl with plt
- replace instances of pl (as on import pylab as pl)
with plt (as in import matplotlib.pyplot as plt)
- bench_sgd_regression.py clean of pl
- code executes properly
* refactor: Replace pl with plt
- replace instances of pl (as on import pylab as pl)
with plt (as in import matplotlib.pyplot as plt)
- bench_tree.py clean of pl
- code executes properly
* docs: removed pylab references from comments
* docs: removed all pylab references
- replaced with matplotlib.pyplot
- pl --> plt
* docs: removed pylab references from comments
- replaced with matplotlib.pyplot
- pl --> plt
* docs: removed all pylab references
- replaced with matplotlib.pyplot
- pl --> plt
* refactor: Replace pl with plt
- replace instances of pl (as on import pylab as pl)
with plt (as in import matplotlib.pyplot as plt)
- mlcomp_sparse_document_classification.py clean of pl
* refactor: Replace pl with plt
- replace instances of pl (as on import pylab as pl)
with plt (as in import matplotlib.pyplot as plt)
- plot_gpr_noisy_targets.py clean of pl
- code does not execute for extraneous reasons
- File "examples/gaussian_process/plot_gpr_noisy_targets.py", line 31, in
<module>
- from sklearn.gaussian_process import GaussianProcessRegressor
- ImportError: cannot import name GaussianProcessRegressor
* refactor: Replace pl with plt
- replace instances of pl (as on import pylab as pl)
with plt (as in import matplotlib.pyplot as plt)
- plot_gpc_isoprobability.py clean of pl
- code does not execute for extraneous reasons
- File "examples/gaussian_process/plot_gpc_isoprobability.py", line 24, in
<module>
- from sklearn.gaussian_process import GaussianProcessClassifier
- ImportError: cannot import name GaussianProcessClassifier
* docs: removed all pylab references
- replaced with matplotlib.pyplot
- pl --> plt
* docs: removed all pylab references
- replaced with matplotlib.pyplot
* refactor: Replace pl with plt
- replace instances of pl (as on import pylab as pl)
with plt (as in import matplotlib.pyplot as plt)
- plot_sparse_coding.py clean of pl
- code executes properly
* docs: removed all pylab references
- replaced with matplotlib.pyplot
* docs: removed all pylab references
- replaced with matplotlib.pyplot
* style: Indent properly
* style: indent properly
* style: Indent properly
* docs: Add missing .pyplot
* docs: Fix typo
* style: Indent properly
* FIX does not draw the ellipse! #6640
* Give ellipses a higher z-order, yellow border, and thicker border.
* Add an alpha level to the markers so that it is easier to tell how
many there are.
* Change false positive to asterisks so that they have similar sizes as
the true positives.
* Fix line too long issue
The comment in a few example plots refer to "the mesh [x_min, m_max] x
[y_min, y_max]" when it should be "x_max".
Also fixed the spacing in plot_random_forest_embedding.py `[x_min,
x_max] x [y_min, y_max]` to `[x_min, x_max]x[y_min, y_max]` to comply
with the coding style of other files with similar code (like those in
the current pull request).
The LDA accronym for Linear Discriminant Analysis is ambiguous
because of the newly introduced Latent Dirichlet Allocation model.
We therefore deprecate the sklearn.lda.LDA and sklearn.lda.QDA
in favor of explicit names.
surgan12