github.com/metaprov/modela-operator@v0.0.0-20240118193048-f378be8b74d2/manifests/modela-catalog/algorithms/classifiers.yaml (about)

     1  apiVersion: catalog.modela.ai/v1alpha1
     2  kind: Algorithm
     3  metadata:
     4    labels:
     5      app.kubernetes.io/part-of: modela
     6    name: ada-boost-classifier
     7    namespace: modela-catalog
     8  spec:
     9    frameworkName: scikit-learn
    10    ranges:
    11    - high: 200
    12      low: 100
    13      name: ada_n_estimators
    14      type: int
    15    - high: 2.0
    16      log: true
    17      low: 0.01
    18      name: ada_learning_rate
    19      type: float
    20    tasks: []
    21  
    22  ---
    23  apiVersion: catalog.modela.ai/v1alpha1
    24  kind: Algorithm
    25  metadata:
    26    labels:
    27      app.kubernetes.io/part-of: modela
    28    name: bernoulli-nb
    29    namespace: modela-catalog
    30  spec:
    31    frameworkName: scikit-learn
    32    ranges:
    33    - high: 100
    34      log: true
    35      low: 0.01
    36      name: br_alpha
    37      type: float
    38    - choices:
    39      - "true"
    40      - "false"
    41      name: br_fit_prior
    42      type: categorical
    43    tasks:
    44    - multi-classification
    45    - binary-classification
    46  
    47  ---
    48  apiVersion: catalog.modela.ai/v1alpha1
    49  kind: Algorithm
    50  metadata:
    51    labels:
    52      app.kubernetes.io/part-of: modela
    53    name: catboost-classifier
    54    namespace: modela-catalog
    55  spec:
    56    frameworkName: scikit-learn
    57    ranges:
    58    - high: 12
    59      low: 1
    60      name: catboost_depth
    61      type: int
    62    - high: 1.0
    63      log: true
    64      low: 0.02
    65      name: catboost_learning_rate
    66      type: float
    67    - choices:
    68      - Bayesian
    69      - Bernoulli
    70      - MVS
    71      name: catboost_bootstrap_type
    72      type: categorical
    73    - choices:
    74      - Plain
    75      - Ordered
    76      name: catboost_boosting_type
    77      type: categorical
    78    - high: 100
    79      low: 10
    80      name: catboost_iterations
    81      type: int
    82    - high: 10
    83      low: 0
    84      name: catboost_bagging_temperature
    85      type: float
    86    - high: 1
    87      low: 0.1
    88      name: catboost_subsample
    89      type: float
    90    tasks:
    91    - multi-classification
    92    - binary-classification
    93  
    94  ---
    95  apiVersion: catalog.modela.ai/v1alpha1
    96  kind: Algorithm
    97  metadata:
    98    labels:
    99      app.kubernetes.io/part-of: modela
   100    name: decision-tree-classifier
   101    namespace: modela-catalog
   102  spec:
   103    frameworkName: scikit-learn
   104    ranges:
   105    - choices:
   106      - gini
   107      - entropy
   108      name: criterion
   109      type: categorical
   110    - high: 10
   111      low: 4
   112      name: dt_max_depth
   113      type: int
   114    - high: 20
   115      low: 2
   116      name: dt_min_samples_split
   117      type: int
   118    - high: 20
   119      low: 1
   120      name: dt_min_samples_leaf
   121      type: int
   122    tasks:
   123    - multi-classification
   124    - binary-classification
   125  
   126  ---
   127  apiVersion: catalog.modela.ai/v1alpha1
   128  kind: Algorithm
   129  metadata:
   130    labels:
   131      app.kubernetes.io/part-of: modela
   132    name: extra-tree-classifier
   133    namespace: modela-catalog
   134  spec:
   135    frameworkName: scikit-learn
   136    ranges:
   137    - high: 20
   138      low: 2
   139      name: et_min_samples_split
   140      type: int
   141    - high: 1.0
   142      log: true
   143      low: 0.1
   144      name: et_max_features
   145      type: float
   146    - high: 20
   147      low: 1
   148      name: et_min_samples_leaf
   149      type: int
   150    tasks:
   151    - multi-classification
   152    - binary-classification
   153  
   154  ---
   155  apiVersion: catalog.modela.ai/v1alpha1
   156  kind: Algorithm
   157  metadata:
   158    labels:
   159      app.kubernetes.io/part-of: modela
   160    name: gaussian-nb
   161    namespace: modela-catalog
   162  spec:
   163    frameworkName: scikit-learn
   164    ranges: []
   165    tasks:
   166    - multi-classification
   167    - binary-classification
   168  
   169  ---
   170  apiVersion: catalog.modela.ai/v1alpha1
   171  kind: Algorithm
   172  metadata:
   173    labels:
   174      app.kubernetes.io/part-of: modela
   175    name: gradient-boosting-classifier
   176    namespace: modela-catalog
   177  spec:
   178    frameworkName: scikit-learn
   179    ranges:
   180    - high: 0.2
   181      log: true
   182      low: 0.001
   183      name: gb_learning_rate
   184      type: float
   185    - high: 200
   186      low: 100
   187      name: gb_n_estimators
   188      type: int
   189    - high: 7
   190      low: 2
   191      name: gb_max_leaf_nodes
   192      type: int
   193    - high: 9
   194      low: 1
   195      name: gb_min_samples_leaf
   196      type: int
   197    - high: 10
   198      low: 4
   199      name: gb_max_depth
   200      type: int
   201    - high: 10
   202      low: 2
   203      name: gb_min_samples_split
   204      type: int
   205    tasks:
   206    - multi-classification
   207    - binary-classification
   208  
   209  ---
   210  apiVersion: catalog.modela.ai/v1alpha1
   211  kind: Algorithm
   212  metadata:
   213    labels:
   214      app.kubernetes.io/part-of: modela
   215    name: hist-gradient-boosting
   216    namespace: modela-catalog
   217  spec:
   218    frameworkName: scikit-learn
   219    ranges:
   220    - high: 0.2
   221      log: true
   222      low: 0.001
   223      name: hg_learning_rate
   224      type: float
   225    - high: 200
   226      low: 100
   227      name: hg_max_iter
   228      type: int
   229    - high: 7
   230      low: 2
   231      name: hg_max_leaf_nodes
   232      type: int
   233    - high: 9
   234      low: 1
   235      name: hg_min_samples_leaf
   236      type: int
   237    tasks:
   238    - multi-classification
   239    - binary-classification
   240  
   241  ---
   242  apiVersion: catalog.modela.ai/v1alpha1
   243  kind: Algorithm
   244  metadata:
   245    labels:
   246      app.kubernetes.io/part-of: modela
   247    name: knn-classifier
   248    namespace: modela-catalog
   249  spec:
   250    frameworkName: scikit-learn
   251    ranges:
   252    - high: 20
   253      low: 1
   254      name: knn_n_neighbors
   255      type: int
   256    - choices:
   257      - uniform
   258      - distance
   259      name: knn_weights
   260      type: categorical
   261    tasks:
   262    - multi-classification
   263    - binary-classification
   264  
   265  ---
   266  apiVersion: catalog.modela.ai/v1alpha1
   267  kind: Algorithm
   268  metadata:
   269    labels:
   270      app.kubernetes.io/part-of: modela
   271    name: linear-discriminant
   272    namespace: modela-catalog
   273  spec:
   274    frameworkName: scikit-learn
   275    ranges: []
   276    tasks:
   277    - multi-classification
   278    - binary-classification
   279  
   280  ---
   281  apiVersion: catalog.modela.ai/v1alpha1
   282  kind: Algorithm
   283  metadata:
   284    labels:
   285      app.kubernetes.io/part-of: modela
   286    name: lightgbm-classifier
   287    namespace: modela-catalog
   288  spec:
   289    frameworkName: lightgbm
   290    ranges:
   291    - choices:
   292      - gbdt
   293      - dart
   294      name: lgbm_boosting_type
   295      type: categorical
   296    - high: 10
   297      low: 4
   298      name: lgbm_max_depth
   299      type: int
   300    - high: 1.0
   301      log: true
   302      low: 0.02
   303      name: lgbm_learning_rate
   304      type: float
   305    - high: 150
   306      low: 50
   307      name: lgbm_n_estimators
   308      type: int
   309    - high: 0.01
   310      low: 0.001
   311      name: lgbm_min_child_weight
   312      type: float
   313    - high: 30
   314      low: 5
   315      name: lgbm_min_child_samples
   316      type: int
   317    - high: 1
   318      log: true
   319      low: 0.01
   320      name: lgbm_subsample
   321      type: float
   322    - high: 5
   323      low: 0
   324      name: lgbm_subsample_freq
   325      type: int
   326    - high: 1.0
   327      log: true
   328      low: 0.01
   329      name: lgbm_colsample_bytree
   330      type: float
   331    - high: 1.0
   332      log: true
   333      low: 0.0
   334      name: lgbm_reg_alpha
   335      type: float
   336    - high: 1.0
   337      log: true
   338      low: 0.0
   339      name: lgbm_reg_lambda
   340      type: float
   341    tasks:
   342    - multi-classification
   343    - binary-classification
   344  
   345  ---
   346  apiVersion: catalog.modela.ai/v1alpha1
   347  kind: Algorithm
   348  metadata:
   349    labels:
   350      app.kubernetes.io/part-of: modela
   351    name: linear-svc
   352    namespace: modela-catalog
   353  spec:
   354    frameworkName: scikit-learn
   355    ranges:
   356    - high: 32768
   357      log: true
   358      low: 0.03125
   359      name: svc_C
   360      type: float
   361    - high: 5
   362      low: 2
   363      name: svc_degree
   364      type: int
   365    - high: 8
   366      log: true
   367      low: 3.0517578125e-05
   368      name: svc_gamma
   369      type: float
   370    - high: 1
   371      log: true
   372      low: -1
   373      name: svc_coef0
   374      type: float
   375    tasks:
   376    - multi-classification
   377    - binary-classification
   378  
   379  ---
   380  apiVersion: catalog.modela.ai/v1alpha1
   381  kind: Algorithm
   382  metadata:
   383    labels:
   384      app.kubernetes.io/part-of: modela
   385    name: logistic-regression
   386    namespace: modela-catalog
   387  spec:
   388    frameworkName: scikit-learn
   389    ranges:
   390    - choices:
   391      - newton-cg
   392      - lbfgs
   393      - liblinear
   394      - sag
   395      - saga
   396      name: logreg_solver
   397      type: categorical
   398    - choices:
   399      - none
   400      - l2
   401      name: logreg_penalty_cg
   402      type: categorical
   403    - choices:
   404      - none
   405      - l2
   406      name: logreg_penalty_lbfgs
   407      type: categorical
   408    - choices:
   409      - l2
   410      - l1
   411      name: logreg_penalty_liblinear
   412      type: categorical
   413    - choices:
   414      - none
   415      - l2
   416      name: logreg_penalty_sag
   417      type: categorical
   418    - choices:
   419      - elasticnet
   420      - l1
   421      - l2
   422      - none
   423      name: logreg_saga
   424      type: categorical
   425    - choices:
   426      - "true"
   427      - "false"
   428      name: logreg_dual
   429      type: categorical
   430    - high: 1.0
   431      log: true
   432      low: 0
   433      name: logreg_l1_ratio
   434      type: float
   435    - high: 10.0
   436      log: true
   437      low: 1.0e-07
   438      name: logreg_C
   439      type: float
   440    - choices:
   441      - "true"
   442      - "false"
   443      name: logreg_fit_intercept
   444      type: categorical
   445    tasks:
   446    - multi-classification
   447    - binary-classification
   448  
   449  ---
   450  apiVersion: catalog.modela.ai/v1alpha1
   451  kind: Algorithm
   452  metadata:
   453    labels:
   454      app.kubernetes.io/part-of: modela
   455    name: multinomial-nb
   456    namespace: modela-catalog
   457  spec:
   458    frameworkName: scikit-learn
   459    ranges:
   460    - high: 100
   461      log: true
   462      low: 0.01
   463      name: multinb_alpha
   464      type: float
   465    - choices:
   466      - "true"
   467      - "false"
   468      name: multinb_fit_prior
   469      type: categorical
   470    tasks:
   471    - multi-classification
   472    - binary-classification
   473  
   474  ---
   475  apiVersion: catalog.modela.ai/v1alpha1
   476  kind: Algorithm
   477  metadata:
   478    labels:
   479      app.kubernetes.io/part-of: modela
   480    name: passive-aggressive-classifier
   481    namespace: modela-catalog
   482  spec:
   483    frameworkName: scikit-learn
   484    ranges:
   485    - high: 10
   486      log: true
   487      low: 0.03125
   488      name: pa_C
   489      type: float
   490    - choices:
   491      - hinge
   492      - squared_hinge
   493      name: pa_loss
   494      type: categorical
   495    tasks:
   496    - multi-classification
   497    - binary-classification
   498  
   499  ---
   500  apiVersion: catalog.modela.ai/v1alpha1
   501  kind: Algorithm
   502  metadata:
   503    labels:
   504      app.kubernetes.io/part-of: modela
   505    name: random-forest-classifier
   506    namespace: modela-catalog
   507  spec:
   508    frameworkName: scikit-learn
   509    ranges:
   510    - high: 2000
   511      low: 200
   512      name: rf_n_estimators
   513      type: int
   514    - high: 20
   515      low: 2
   516      name: rf_min_samples_split
   517      type: int
   518    - high: 1.0
   519      log: true
   520      low: 0.1
   521      name: rf_max_features
   522      type: float
   523    - high: 20
   524      low: 1
   525      name: rf_min_samples_leaf
   526      type: int
   527    tasks:
   528    - multi-classification
   529    - binary-classification
   530  
   531  ---
   532  apiVersion: catalog.modela.ai/v1alpha1
   533  kind: Algorithm
   534  metadata:
   535    labels:
   536      app.kubernetes.io/part-of: modela
   537    name: sgd-classifier
   538    namespace: modela-catalog
   539  spec:
   540    frameworkName: scikit-learn
   541    ranges:
   542    - choices:
   543      - log
   544      - modified_huber
   545      name: sgd_loss
   546      type: categorical
   547    - choices:
   548      - l1
   549      - l2
   550      - elasticnet
   551      name: sgd_penalty
   552      type: categorical
   553    - high: 0.1
   554      log: true
   555      low: 1.0e-07
   556      name: sgd_alpha
   557      type: float
   558    - choices:
   559      - optimal
   560      - invscaling
   561      - constant
   562      name: sgd_learning_rate
   563      type: categorical
   564    - high: 1
   565      log: true
   566      low: 1.0e-09
   567      name: sgd_l1_ratio
   568      type: float
   569    - high: 0.1
   570      log: true
   571      low: 1.0e-07
   572      name: sgd_eta0
   573      type: float
   574    - high: 1
   575      log: true
   576      low: 1.0e-05
   577      name: sgd_power_t
   578      type: float
   579    tasks:
   580    - multi-classification
   581    - binary-classification
   582  
   583  ---
   584  apiVersion: catalog.modela.ai/v1alpha1
   585  kind: Algorithm
   586  metadata:
   587    labels:
   588      app.kubernetes.io/part-of: modela
   589    name: svc
   590    namespace: modela-catalog
   591  spec:
   592    frameworkName: scikit-learn
   593    ranges:
   594    - high: 32768
   595      log: true
   596      low: 0.03125
   597      name: svc_C
   598      type: float
   599    - choices:
   600      - rbf
   601      - poly
   602      - sigmoid
   603      name: svc_kernel
   604      type: categorical
   605    - high: 5
   606      low: 2
   607      name: svc_degree
   608      type: int
   609    - high: 8
   610      log: true
   611      low: 3.0517578125e-05
   612      name: svc_gamma
   613      type: float
   614    - high: 1
   615      log: true
   616      low: -1
   617      name: svc_coef0
   618      type: float
   619    - choices:
   620      - "true"
   621      - "false"
   622      name: svc_shrinking
   623      type: categorical
   624    - high: 0.1
   625      log: true
   626      low: 1.0e-05
   627      name: svc_tol
   628      type: float
   629    tasks:
   630    - multi-classification
   631    - binary-classification
   632  
   633  ---
   634  apiVersion: catalog.modela.ai/v1alpha1
   635  kind: Algorithm
   636  metadata:
   637    labels:
   638      app.kubernetes.io/part-of: modela
   639    name: xgboost-classifier
   640    namespace: modela-catalog
   641  spec:
   642    frameworkName: xgboost
   643    ranges:
   644    - high: 1024
   645      log: true
   646      low: 64
   647      name: xgb_num_round
   648      type: float
   649    - high: 8
   650      low: 2
   651      name: xgb_max_depth
   652      type: int
   653    - high: 1
   654      log: true
   655      low: 0.01
   656      name: xgb_eta
   657      type: float
   658    - high: 64.0
   659      log: true
   660      low: 1.0e-06
   661      name: xgb_gamma
   662      type: float
   663    - high: 32.0
   664      log: true
   665      low: 1.0e-06
   666      name: xgb_min_child_weight
   667      type: float
   668    - high: 1.0
   669      log: true
   670      low: 0.5
   671      name: xgb_subsample
   672      type: float
   673    - high: 1.0
   674      log: true
   675      low: 0.3
   676      name: xgb_colsample_bytree
   677      type: float
   678    - high: 2.0
   679      log: true
   680      low: 1.0e-06
   681      name: xgb_lambda
   682      type: float
   683    - high: 2.0
   684      log: true
   685      low: 1.0e-06
   686      name: xgb_alpha
   687      type: float
   688    - high: 0.01
   689      log: true
   690      low: 1.0e-06
   691      name: xgb_learning_rate
   692      type: float
   693    tasks:
   694    - multi-classification
   695    - binary-classification