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pushing files to the repo from the example!

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  1. NYC_SQF_ARR_RF_no_race_no_sex.pkl +3 -0
  2. README.md +377 -0
  3. config.json +322 -0
NYC_SQF_ARR_RF_no_race_no_sex.pkl ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:7442c31c8c2c9863d08ce6ffb039cf99c054067ff9cf940423713a64f470e25d
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+ size 25617027
README.md ADDED
@@ -0,0 +1,377 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ library_name: sklearn
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+ tags:
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+ - sklearn
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+ - skops
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+ - tabular-classification
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+ model_format: pickle
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+ model_file: NYC_SQF_ARR_RF_no_race_no_sex.pkl
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+ widget:
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+ - structuredData:
11
+ ASK_FOR_CONSENT_FLG_(null):
12
+ - 0
13
+ - 0
14
+ - 0
15
+ ASK_FOR_CONSENT_FLG_N:
16
+ - 1
17
+ - 1
18
+ - 1
19
+ ASK_FOR_CONSENT_FLG_Y:
20
+ - 0
21
+ - 0
22
+ - 0
23
+ CONSENT_GIVEN_FLG_(null):
24
+ - 0
25
+ - 1
26
+ - 0
27
+ CONSENT_GIVEN_FLG_N:
28
+ - 1
29
+ - 0
30
+ - 1
31
+ CONSENT_GIVEN_FLG_Y:
32
+ - 0
33
+ - 0
34
+ - 0
35
+ FIREARM_FLAG:
36
+ - 0
37
+ - 0
38
+ - 0
39
+ FRISKED_FLAG:
40
+ - 0
41
+ - 1
42
+ - 1
43
+ ISSUING_OFFICER_RANK_CPT:
44
+ - 0
45
+ - 0
46
+ - 0
47
+ ISSUING_OFFICER_RANK_DI:
48
+ - 0
49
+ - 0
50
+ - 0
51
+ ISSUING_OFFICER_RANK_DT1:
52
+ - 0
53
+ - 0
54
+ - 0
55
+ ISSUING_OFFICER_RANK_DT2:
56
+ - 0
57
+ - 0
58
+ - 0
59
+ ISSUING_OFFICER_RANK_DT3:
60
+ - 0
61
+ - 0
62
+ - 0
63
+ ISSUING_OFFICER_RANK_DTS:
64
+ - 0
65
+ - 0
66
+ - 0
67
+ ISSUING_OFFICER_RANK_INS:
68
+ - 0
69
+ - 0
70
+ - 0
71
+ ISSUING_OFFICER_RANK_LSA:
72
+ - 0
73
+ - 0
74
+ - 0
75
+ ISSUING_OFFICER_RANK_LT:
76
+ - 0
77
+ - 0
78
+ - 0
79
+ ISSUING_OFFICER_RANK_PO:
80
+ - 1
81
+ - 1
82
+ - 1
83
+ ISSUING_OFFICER_RANK_POF:
84
+ - 0
85
+ - 0
86
+ - 0
87
+ ISSUING_OFFICER_RANK_POM:
88
+ - 0
89
+ - 0
90
+ - 0
91
+ ISSUING_OFFICER_RANK_SDS:
92
+ - 0
93
+ - 0
94
+ - 0
95
+ ISSUING_OFFICER_RANK_SGT:
96
+ - 0
97
+ - 0
98
+ - 0
99
+ ISSUING_OFFICER_RANK_SSA:
100
+ - 0
101
+ - 0
102
+ - 0
103
+ KNIFE_CUTTER_FLAG:
104
+ - 0
105
+ - 0
106
+ - 0
107
+ OTHER_CONTRABAND_FLAG:
108
+ - 0
109
+ - 0
110
+ - 0
111
+ OTHER_WEAPON_FLAG:
112
+ - 0
113
+ - 0
114
+ - 0
115
+ SEARCHED_FLAG:
116
+ - 0
117
+ - 0
118
+ - 1
119
+ STOP_LOCATION_PRECINCT:
120
+ - 20
121
+ - 23
122
+ - 46
123
+ SUPERVISING_OFFICER_RANK_CPT:
124
+ - 0
125
+ - 0
126
+ - 0
127
+ SUPERVISING_OFFICER_RANK_DI:
128
+ - 0
129
+ - 0
130
+ - 0
131
+ SUPERVISING_OFFICER_RANK_DT3:
132
+ - 0
133
+ - 0
134
+ - 0
135
+ SUPERVISING_OFFICER_RANK_DTS:
136
+ - 0
137
+ - 0
138
+ - 0
139
+ SUPERVISING_OFFICER_RANK_INS:
140
+ - 0
141
+ - 0
142
+ - 0
143
+ SUPERVISING_OFFICER_RANK_LCD:
144
+ - 0
145
+ - 0
146
+ - 0
147
+ SUPERVISING_OFFICER_RANK_LSA:
148
+ - 0
149
+ - 0
150
+ - 0
151
+ SUPERVISING_OFFICER_RANK_LT:
152
+ - 0
153
+ - 0
154
+ - 0
155
+ SUPERVISING_OFFICER_RANK_PO:
156
+ - 0
157
+ - 0
158
+ - 0
159
+ SUPERVISING_OFFICER_RANK_POF:
160
+ - 0
161
+ - 0
162
+ - 0
163
+ SUPERVISING_OFFICER_RANK_POM:
164
+ - 0
165
+ - 0
166
+ - 0
167
+ SUPERVISING_OFFICER_RANK_SDS:
168
+ - 0
169
+ - 0
170
+ - 0
171
+ SUPERVISING_OFFICER_RANK_SGT:
172
+ - 1
173
+ - 1
174
+ - 1
175
+ SUPERVISING_OFFICER_RANK_SSA:
176
+ - 0
177
+ - 0
178
+ - 0
179
+ SUSPECT_BODY_BUILD_TYPE_(null):
180
+ - 0
181
+ - 0
182
+ - 0
183
+ SUSPECT_BODY_BUILD_TYPE_HEA:
184
+ - 0
185
+ - 0
186
+ - 0
187
+ SUSPECT_BODY_BUILD_TYPE_MED:
188
+ - 0
189
+ - 1
190
+ - 1
191
+ SUSPECT_BODY_BUILD_TYPE_THN:
192
+ - 1
193
+ - 0
194
+ - 0
195
+ SUSPECT_BODY_BUILD_TYPE_U:
196
+ - 0
197
+ - 0
198
+ - 0
199
+ SUSPECT_BODY_BUILD_TYPE_XXX:
200
+ - 0
201
+ - 0
202
+ - 0
203
+ SUSPECT_HEIGHT:
204
+ - 5.7
205
+ - 5.9
206
+ - 5.1
207
+ SUSPECT_REPORTED_AGE:
208
+ - 30.0
209
+ - 28.0
210
+ - 24.0
211
+ SUSPECT_WEIGHT:
212
+ - 160.0
213
+ - 175.0
214
+ - 210.0
215
+ ---
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+
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+ # Model description
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+
219
+ [More Information Needed]
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+
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+ ## Intended uses & limitations
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+
223
+ [More Information Needed]
224
+
225
+ ## Training Procedure
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+
227
+ [More Information Needed]
228
+
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+ ### Hyperparameters
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+
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+ <details>
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+ <summary> Click to expand </summary>
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+
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+ | Hyperparameter | Value |
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+ |-------------------------------|-------------------------------------|
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+ | memory | |
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+ | steps | [('clf', RandomForestClassifier())] |
238
+ | verbose | False |
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+ | clf | RandomForestClassifier() |
240
+ | clf__bootstrap | True |
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+ | clf__ccp_alpha | 0.0 |
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+ | clf__class_weight | |
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+ | clf__criterion | gini |
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+ | clf__max_depth | |
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+ | clf__max_features | sqrt |
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+ | clf__max_leaf_nodes | |
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+ | clf__max_samples | |
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+ | clf__min_impurity_decrease | 0.0 |
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+ | clf__min_samples_leaf | 1 |
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+ | clf__min_samples_split | 2 |
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+ | clf__min_weight_fraction_leaf | 0.0 |
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+ | clf__monotonic_cst | |
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+ | clf__n_estimators | 100 |
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+ | clf__n_jobs | |
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+ | clf__oob_score | False |
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+ | clf__random_state | |
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+ | clf__verbose | 0 |
258
+ | clf__warm_start | False |
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+
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+ </details>
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+
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+ ### Model Plot
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+
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+ <style>#sk-container-id-2 {/* Definition of color scheme common for light and dark mode */--sklearn-color-text: black;--sklearn-color-line: gray;/* Definition of color scheme for unfitted estimators */--sklearn-color-unfitted-level-0: #fff5e6;--sklearn-color-unfitted-level-1: #f6e4d2;--sklearn-color-unfitted-level-2: #ffe0b3;--sklearn-color-unfitted-level-3: chocolate;/* Definition of color scheme for fitted estimators */--sklearn-color-fitted-level-0: #f0f8ff;--sklearn-color-fitted-level-1: #d4ebff;--sklearn-color-fitted-level-2: #b3dbfd;--sklearn-color-fitted-level-3: cornflowerblue;/* Specific color for light theme */--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));--sklearn-color-icon: #696969;@media (prefers-color-scheme: dark) {/* Redefinition of color scheme for dark theme */--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));--sklearn-color-icon: #878787;}
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+ }#sk-container-id-2 {color: var(--sklearn-color-text);
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+ }#sk-container-id-2 pre {padding: 0;
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+ }#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;
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+ }#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed var(--sklearn-color-line);margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: var(--sklearn-color-background);
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+ }#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }`but bootstrap.min.css set `[hidden] { display: none !important; }`so we also need the `!important` here to be able to override thedefault hidden behavior on the sphinx rendered scikit-learn.org.See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;
270
+ }#sk-container-id-2 div.sk-text-repr-fallback {display: none;
271
+ }div.sk-parallel-item,
272
+ div.sk-serial,
273
+ div.sk-item {/* draw centered vertical line to link estimators */background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));background-size: 2px 100%;background-repeat: no-repeat;background-position: center center;
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+ }/* Parallel-specific style estimator block */#sk-container-id-2 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 2px solid var(--sklearn-color-text-on-default-background);flex-grow: 1;
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+ }#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: var(--sklearn-color-background);position: relative;
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+ }#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;
277
+ }#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;
278
+ }#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;
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+ }#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;
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+ }/* Serial-specific style estimator block */#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: var(--sklearn-color-background);padding-right: 1em;padding-left: 1em;
281
+ }/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
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+ clickable and can be expanded/collapsed.
283
+ - Pipeline and ColumnTransformer use this feature and define the default style
284
+ - Estimators will overwrite some part of the style using the `sk-estimator` class
285
+ *//* Pipeline and ColumnTransformer style (default) */#sk-container-id-2 div.sk-toggleable {/* Default theme specific background. It is overwritten whether we have aspecific estimator or a Pipeline/ColumnTransformer */background-color: var(--sklearn-color-background);
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+ }/* Toggleable label */
287
+ #sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.5em;box-sizing: border-box;text-align: center;
288
+ }#sk-container-id-2 label.sk-toggleable__label-arrow:before {/* Arrow on the left of the label */content: "▸";float: left;margin-right: 0.25em;color: var(--sklearn-color-icon);
289
+ }#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: var(--sklearn-color-text);
290
+ }/* Toggleable content - dropdown */#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;/* unfitted */background-color: var(--sklearn-color-unfitted-level-0);
291
+ }#sk-container-id-2 div.sk-toggleable__content.fitted {/* fitted */background-color: var(--sklearn-color-fitted-level-0);
292
+ }#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;border-radius: 0.25em;color: var(--sklearn-color-text);/* unfitted */background-color: var(--sklearn-color-unfitted-level-0);
293
+ }#sk-container-id-2 div.sk-toggleable__content.fitted pre {/* unfitted */background-color: var(--sklearn-color-fitted-level-0);
294
+ }#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {/* Expand drop-down */max-height: 200px;max-width: 100%;overflow: auto;
295
+ }#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";
296
+ }/* Pipeline/ColumnTransformer-specific style */#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {color: var(--sklearn-color-text);background-color: var(--sklearn-color-unfitted-level-2);
297
+ }#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: var(--sklearn-color-fitted-level-2);
298
+ }/* Estimator-specific style *//* Colorize estimator box */
299
+ #sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {/* unfitted */background-color: var(--sklearn-color-unfitted-level-2);
300
+ }#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {/* fitted */background-color: var(--sklearn-color-fitted-level-2);
301
+ }#sk-container-id-2 div.sk-label label.sk-toggleable__label,
302
+ #sk-container-id-2 div.sk-label label {/* The background is the default theme color */color: var(--sklearn-color-text-on-default-background);
303
+ }/* On hover, darken the color of the background */
304
+ #sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {color: var(--sklearn-color-text);background-color: var(--sklearn-color-unfitted-level-2);
305
+ }/* Label box, darken color on hover, fitted */
306
+ #sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {color: var(--sklearn-color-text);background-color: var(--sklearn-color-fitted-level-2);
307
+ }/* Estimator label */#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;
308
+ }#sk-container-id-2 div.sk-label-container {text-align: center;
309
+ }/* Estimator-specific */
310
+ #sk-container-id-2 div.sk-estimator {font-family: monospace;border: 1px dotted var(--sklearn-color-border-box);border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;/* unfitted */background-color: var(--sklearn-color-unfitted-level-0);
311
+ }#sk-container-id-2 div.sk-estimator.fitted {/* fitted */background-color: var(--sklearn-color-fitted-level-0);
312
+ }/* on hover */
313
+ #sk-container-id-2 div.sk-estimator:hover {/* unfitted */background-color: var(--sklearn-color-unfitted-level-2);
314
+ }#sk-container-id-2 div.sk-estimator.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-2);
315
+ }/* Specification for estimator info (e.g. "i" and "?") *//* Common style for "i" and "?" */.sk-estimator-doc-link,
316
+ a:link.sk-estimator-doc-link,
317
+ a:visited.sk-estimator-doc-link {float: right;font-size: smaller;line-height: 1em;font-family: monospace;background-color: var(--sklearn-color-background);border-radius: 1em;height: 1em;width: 1em;text-decoration: none !important;margin-left: 1ex;/* unfitted */border: var(--sklearn-color-unfitted-level-1) 1pt solid;color: var(--sklearn-color-unfitted-level-1);
318
+ }.sk-estimator-doc-link.fitted,
319
+ a:link.sk-estimator-doc-link.fitted,
320
+ a:visited.sk-estimator-doc-link.fitted {/* fitted */border: var(--sklearn-color-fitted-level-1) 1pt solid;color: var(--sklearn-color-fitted-level-1);
321
+ }/* On hover */
322
+ div.sk-estimator:hover .sk-estimator-doc-link:hover,
323
+ .sk-estimator-doc-link:hover,
324
+ div.sk-label-container:hover .sk-estimator-doc-link:hover,
325
+ .sk-estimator-doc-link:hover {/* unfitted */background-color: var(--sklearn-color-unfitted-level-3);color: var(--sklearn-color-background);text-decoration: none;
326
+ }div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
327
+ .sk-estimator-doc-link.fitted:hover,
328
+ div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
329
+ .sk-estimator-doc-link.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-3);color: var(--sklearn-color-background);text-decoration: none;
330
+ }/* Span, style for the box shown on hovering the info icon */
331
+ .sk-estimator-doc-link span {display: none;z-index: 9999;position: relative;font-weight: normal;right: .2ex;padding: .5ex;margin: .5ex;width: min-content;min-width: 20ex;max-width: 50ex;color: var(--sklearn-color-text);box-shadow: 2pt 2pt 4pt #999;/* unfitted */background: var(--sklearn-color-unfitted-level-0);border: .5pt solid var(--sklearn-color-unfitted-level-3);
332
+ }.sk-estimator-doc-link.fitted span {/* fitted */background: var(--sklearn-color-fitted-level-0);border: var(--sklearn-color-fitted-level-3);
333
+ }.sk-estimator-doc-link:hover span {display: block;
334
+ }/* "?"-specific style due to the `<a>` HTML tag */#sk-container-id-2 a.estimator_doc_link {float: right;font-size: 1rem;line-height: 1em;font-family: monospace;background-color: var(--sklearn-color-background);border-radius: 1rem;height: 1rem;width: 1rem;text-decoration: none;/* unfitted */color: var(--sklearn-color-unfitted-level-1);border: var(--sklearn-color-unfitted-level-1) 1pt solid;
335
+ }#sk-container-id-2 a.estimator_doc_link.fitted {/* fitted */border: var(--sklearn-color-fitted-level-1) 1pt solid;color: var(--sklearn-color-fitted-level-1);
336
+ }/* On hover */
337
+ #sk-container-id-2 a.estimator_doc_link:hover {/* unfitted */background-color: var(--sklearn-color-unfitted-level-3);color: var(--sklearn-color-background);text-decoration: none;
338
+ }#sk-container-id-2 a.estimator_doc_link.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-3);
339
+ }
340
+ </style><div id="sk-container-id-2" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[(&#x27;clf&#x27;, RandomForestClassifier())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-3" type="checkbox" ><label for="sk-estimator-id-3" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;&nbsp;Pipeline<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html">?<span>Documentation for Pipeline</span></a><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></label><div class="sk-toggleable__content fitted"><pre>Pipeline(steps=[(&#x27;clf&#x27;, RandomForestClassifier())])</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-4" type="checkbox" ><label for="sk-estimator-id-4" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;RandomForestClassifier<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.RandomForestClassifier.html">?<span>Documentation for RandomForestClassifier</span></a></label><div class="sk-toggleable__content fitted"><pre>RandomForestClassifier()</pre></div> </div></div></div></div></div></div>
341
+
342
+ ## Evaluation Results
343
+
344
+ | Metric | Value |
345
+ |-----------|---------|
346
+ | accuracy | 0 |
347
+ | f1 score | 0 |
348
+ | precision | 0 |
349
+ | recall | 0 |
350
+
351
+ # How to Get Started with the Model
352
+
353
+ [More Information Needed]
354
+
355
+ # Model Card Authors
356
+
357
+ This model card is written by following authors:
358
+
359
+ [More Information Needed]
360
+
361
+ # Model Card Contact
362
+
363
+ You can contact the model card authors through following channels:
364
+ [More Information Needed]
365
+
366
+ # Citation
367
+
368
+ Below you can find information related to citation.
369
+
370
+ **BibTeX:**
371
+ ```
372
+ [More Information Needed]
373
+ ```
374
+
375
+ # eval_method
376
+
377
+ The model is evaluated using test split, on accuracy, precision, recall and f1.
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+ },
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+ "model_format": "pickle",
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+ "task": "tabular-classification"
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+ }
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+ }