Locality Filter All Mindanao records · 4500 of 4500 records
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Per-Question (Indicator-Level) Classification Review
Currently selected question
Barangay roads
The cards below place this question alongside other questions from the selected service stage, so its evidence strength can be compared fairly.
How to read this result
Start with “Ready for interpretation.” Treat “Use with caution” as supporting evidence, and do not make strong claims from indicators that need stronger evidence.
- Public markets and satellite markets
- Barangay hall
- Barangay roads
- Public Cemetery
- Sports centers and facilities
- Road Safety
- Municipal Government Buildings
- Flood Control Management System
- Public parks and open spaces
- Multipurpose halls or civic centers
- Municipal roads and bridges
- Information and reading center
Technical and methodology notes
Available data: The current dataset does not include direct access-barrier variables such as distance, waiting time, facility supply, staff interaction, or household service need. The portal should therefore improve the existing evidence first instead of inventing unavailable predictors.
Eligible responses: Stage-specific modeling is applied through the saved stage response files and skip-pattern handling: Awareness uses valid awareness responses; Availment uses the availment stage; Satisfaction and Need for Action are interpreted only for respondents who reached the service-use stage.
Predictor selection: The decision-tree pipeline now enriches the general profile and citizen-segment predictors with available service-context evidence when applicable: health background variables for Health Services, education background variables for Support to Education, and crime, disaster, corruption, and citizen-attitude evidence for Governance and Response. Feature selection remains part of the model search, while chi-square is kept in the citizen segment evidence area as profile-cluster support.
Model comparison: Recommended model comparison: keep Decision Tree as the official explanation model, then add Random Forest as a performance benchmark and Logistic Regression as a simple baseline. If another model improves ROC AUC or recall, report it as supporting evidence while keeping the decision tree for readable rules.
What the Model Found
For Public Works and Infrastructure - Awareness, the summary combines 12 indicator-specific decision-tree model(s). Mean F1 is 62.0% and mean ROC AUC is 55.0%, so the result should be read as an overall tendency across indicators. The indicator-level rows remain the main evidence for decision-support use.
Use the mean scores for the general story; use the indicator rows for the actual evidence.
Stage eligibility is handled before modeling: Awareness uses all valid Yes/No responses; Availment uses Awareness = Yes; Satisfaction and Need for Action use Awareness = Yes and Availment = Yes. Skip-pattern values such as 95-99 are excluded from the target class.
- Mean precision is 77.3%, indicating strong when an indicator model predicts the positive service outcome.
- Mean recall is 55.1%, meaning some indicator models may still miss actual positive cases, especially when recall is lower than precision.
- Mean F1 score is 62.0%, which balances precision and recall across the indicator models.
- Mean ROC AUC is 55.0%, showing how well the indicator models separate outcome groups across thresholds on average.
- Top predictors currently include MCA DimMagnitude, MCA Dim2, Source of Drinking Water, MCA Dim1, Source of Information. These variables are useful signals for explaining which respondent profiles are linked to the selected service outcome.
- Interpretation: the model is more reliable when it says a respondent group is positive, but it may miss some groups that also belong to that outcome. Use it to prioritize follow-up, not to exclude citizens from attention.
Key Influencing Factors
-
Barangay roads
MCA DimMagnitude -
Barangay roads
MCA Dim2 -
Barangay roads
Source of Drinking Water -
Municipal roads and bridges
MCA DimMagnitude -
Municipal roads and bridges
MCA Dim1 -
Municipal roads and bridges
MCA Dim2 -
Barangay hall
Source of Information -
Barangay hall
MCA Dim1
Key-Factor Strength Chart
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Key Influencing Factors
Decision Tree Interpretation
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Evidence Tables
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Optional detail
Evidence Tables
Show readiness review, indicator metrics, rule reference, and diagnostics.
Model Readiness Review
| Indicator | Signal Quality (F1 / ROC AUC / Recall / Baseline) | Meaning | Majority Response (Baseline Class) | Eligible Records | Baseline Accuracy (Majority Guess) | Model Accuracy | Gain (Model - Baseline) | Possible Cause | Suggested Data Improvement |
|---|---|---|---|---|---|---|---|---|---|
| H1_HPIi_A Barangay roads |
Limited signal | The model can be reviewed as an exploratory clue, but F1, ROC AUC, or baseline gain is not strong enough for confident prediction. | Yes / Positive (93.9%) | 4500 | 93.9% | 91.8% | -2.0 pts | The result may be close to the majority-class baseline, meaning the model adds limited separation beyond the most common response. | Add or review awareness-source, barangay information channel, distance, and program availability variables for Public Works and Infrastructure. |
| H1_HPIx Public Cemetery |
Needs more predictors | The model has difficulty separating respondents based on ROC AUC, recall, or F1. | Yes / Positive (85.7%) | 4200 | 85.7% | 69.0% | -16.6 pts | The result may be close to the majority-class baseline, meaning the model adds limited separation beyond the most common response. | Add or review awareness-source, barangay information channel, distance, and program availability variables for Public Works and Infrastructure. |
| H1_HPIvii Sports centers and facilities |
Limited signal | The model can be reviewed as an exploratory clue, but F1, ROC AUC, or baseline gain is not strong enough for confident prediction. | Yes / Positive (76.3%) | 4200 | 76.3% | 58.1% | -18.2 pts | The result may be close to the majority-class baseline, meaning the model adds limited separation beyond the most common response. | Add or review awareness-source, barangay information channel, distance, and program availability variables for Public Works and Infrastructure. |
| H1_HPIvi Road Safety |
Limited signal | The model can be reviewed as an exploratory clue, but F1, ROC AUC, or baseline gain is not strong enough for confident prediction. | Yes / Positive (64.4%) | 4500 | 64.4% | 56.0% | -8.4 pts | The result may be close to the majority-class baseline, meaning the model adds limited separation beyond the most common response. | Add or review awareness-source, barangay information channel, distance, and program availability variables for Public Works and Infrastructure. |
| H1_HPIiv Public markets and satellite markets |
Moderate signal | The model has some useful signal based on F1 and ROC AUC, but separation between outcome groups is still limited. | Yes / Positive (76.1%) | 4200 | 76.1% | 54.3% | -21.8 pts | The result may be close to the majority-class baseline, meaning the model adds limited separation beyond the most common response. | Add or review awareness-source, barangay information channel, distance, and program availability variables for Public Works and Infrastructure. |
| H1_HPIii Barangay hall |
Moderate signal | The model has some useful signal based on F1 and ROC AUC, but separation between outcome groups is still limited. | Yes / Positive (91.3%) | 3900 | 91.3% | 48.5% | -42.8 pts | The result may be close to the majority-class baseline, meaning the model adds limited separation beyond the most common response. | Add or review awareness-source, barangay information channel, distance, and program availability variables for Public Works and Infrastructure. |
| H1_HPIix Municipal Government Buildings |
Needs more predictors | The model has difficulty separating respondents based on ROC AUC, recall, or F1. | Yes / Positive (85.6%) | 4200 | 85.6% | 49.3% | -36.3 pts | The result may be close to the majority-class baseline, meaning the model adds limited separation beyond the most common response. | Add or review awareness-source, barangay information channel, distance, and program availability variables for Public Works and Infrastructure. |
| H1_HPIxi Flood Control Management System |
Needs more predictors | The model has difficulty separating respondents based on ROC AUC, recall, or F1. | Yes / Positive (65.8%) | 4350 | 65.8% | 53.9% | -11.9 pts | The result may be close to the majority-class baseline, meaning the model adds limited separation beyond the most common response. | Add or review awareness-source, barangay information channel, distance, and program availability variables for Public Works and Infrastructure. |
| H1_HPIv Public parks and open spaces |
Needs more predictors | The model has difficulty separating respondents based on ROC AUC, recall, or F1. | Yes / Positive (59.1%) | 4050 | 59.1% | 55.4% | -3.7 pts | The result may be close to the majority-class baseline, meaning the model adds limited separation beyond the most common response. | Add or review awareness-source, barangay information channel, distance, and program availability variables for Public Works and Infrastructure. |
| H1_HPIiii Multipurpose halls or civic centers |
Needs more predictors | The model has difficulty separating respondents based on ROC AUC, recall, or F1. | Yes / Positive (76.3%) | 3900 | 76.3% | 43.8% | -32.5 pts | The result may be close to the majority-class baseline, meaning the model adds limited separation beyond the most common response. | Add or review awareness-source, barangay information channel, distance, and program availability variables for Public Works and Infrastructure. |
| H1_HPIi_B Municipal roads and bridges |
Needs more predictors | The model has difficulty separating respondents based on ROC AUC, recall, or F1. | Yes / Positive (89.1%) | 4200 | 89.1% | 33.0% | -56.0 pts | The result may be close to the majority-class baseline, meaning the model adds limited separation beyond the most common response. | Add or review awareness-source, barangay information channel, distance, and program availability variables for Public Works and Infrastructure. |
| H1_HPIviii Information and reading center |
Needs more predictors | The model has difficulty separating respondents based on ROC AUC, recall, or F1. | No / Negative (70.7%) | 2850 | 70.7% | 51.1% | -19.6 pts | The result may be close to the majority-class baseline, meaning the model adds limited separation beyond the most common response. | Add or review awareness-source, barangay information channel, distance, and program availability variables for Public Works and Infrastructure. |
Indicator-Level Metrics
The AVG values summarize 12 indicator model(s) for Public Works and Infrastructure - Awareness. They describe the overall pattern across indicators, not the result of one specific indicator.
Average F1 is 62.0%, which gives the most balanced quick reading because it considers both correct positive predictions and missed positive cases.
Average ROC AUC is 55.0%, so the model should be read as decision-support evidence. Values closer to 50% mean the predictors have limited ability to separate the outcome groups.
Precision is high at 77.3%, but recall is lower at 55.1%. Positive predictions may be reliable, but the model may still miss some actual positive cases.
| Target | Indicator | Accuracy | Precision | Recall | F1 | ROC AUC | CV F1 | Best CV F1 | Selected Features | Base Predictors | Service Context | Total Predictors | Depth | Leaf | Criterion |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| H1_HPIi_A | Barangay roads | 91.8% | 94.1% | 97.4% | 95.7% | 52.0% | 59.8% | 83.9% | all | 17 | 0 | 17 | 3 | 10 | entropy |
| H1_HPIx | Public Cemetery | 69.0% | 85.7% | 76.7% | 80.9% | 51.1% | 69.9% | 82.2% | 16 | 17 | 0 | 17 | 5 | 35 | entropy |
| H1_HPIvii | Sports centers and facilities | 58.1% | 79.7% | 60.4% | 68.8% | 53.8% | 65.1% | 69.3% | all | 17 | 0 | 17 | 3 | 35 | entropy |
| H1_HPIvi | Road Safety | 56.0% | 67.1% | 62.2% | 64.6% | 54.9% | 63.2% | 64.8% | all | 17 | 0 | 17 | 5 | 35 | entropy |
| H1_HPIiv | Public markets and satellite markets | 54.3% | 80.9% | 52.3% | 63.5% | 56.0% | 68.4% | 74.4% | 8 | 17 | 0 | 17 | 3 | 10 | entropy |
| H1_HPIii | Barangay hall | 48.5% | 94.3% | 46.4% | 62.2% | 60.8% | 70.6% | 79.2% | all | 17 | 0 | 17 | 5 | 35 | entropy |
| H1_HPIix | Municipal Government Buildings | 49.3% | 87.7% | 47.5% | 61.6% | 53.6% | 62.8% | 63.0% | 16 | 17 | 0 | 17 | 6 | 35 | entropy |
| H1_HPIxi | Flood Control Management System | 53.9% | 71.7% | 49.4% | 58.5% | 57.9% | 64.1% | 64.2% | 8 | 17 | 0 | 17 | 6 | 10 | entropy |
| H1_HPIv | Public parks and open spaces | 55.4% | 68.1% | 46.2% | 55.1% | 59.5% | 62.6% | 64.4% | 8 | 17 | 0 | 17 | 6 | 10 | entropy |
| H1_HPIiii | Multipurpose halls or civic centers | 43.8% | 77.6% | 36.9% | 50.0% | 51.8% | 59.8% | 60.4% | 8 | 17 | 0 | 17 | 6 | 35 | gini |
| H1_HPIi_B | Municipal roads and bridges | 33.0% | 89.5% | 28.1% | 42.8% | 53.3% | 73.9% | 74.5% | all | 17 | 0 | 17 | 5 | 10 | entropy |
| H1_HPIviii | Information and reading center | 51.1% | 31.6% | 57.4% | 40.7% | 55.0% | 41.5% | 42.2% | all | 17 | 0 | 17 | 6 | 35 | entropy |
Decision Rule Reference
| Code | Meaning | Code Values / Variable Type | How to Read the Split |
|---|---|---|---|
| Dim2 | MCA profile dimension 2 | A combined respondent-profile score from MCA. It is not a single survey question. | Dim2 <= 2.138 follows one side of the profile map; values above 2.138 follow the other side. |
Gini Split Diagnostics
| Node | Type | Rule | Gini | Samples | Not Aware | Aware | Prediction |
|---|---|---|---|---|---|---|---|
| 0 | Split | Dim2 <= 2.138 | 0.5 | 4500 | 0.5 | 0.5 | Aware |
| 1 | Split | Dim2 <= -1.321 | 0.4999 | 4449 | 0.5 | 0.5 | Aware |
| 2 | Split | Dim2 <= -1.421 | 0.4823 | 421 | 0.4 | 0.6 | Aware |
| 3 | Leaf | Prediction | 0.4999 | 191 | 0.5 | 0.5 | Not Aware |
| 4 | Leaf | Prediction | 0.4124 | 230 | 0.3 | 0.7 | Aware |
| 5 | Split | Dim2 <= -1.310 | 0.5 | 4028 | 0.5 | 0.5 | Not Aware |
| 6 | Leaf | Prediction | 0.3285 | 25 | 0.8 | 0.2 | Not Aware |
| 7 | Leaf | Prediction | 0.5 | 4003 | 0.5 | 0.5 | Aware |
| 8 | Split | Dim2 <= 2.293 | 0.3581 | 51 | 0.8 | 0.2 | Not Aware |
| 9 | Leaf | Prediction | 0.2841 | 25 | 0.8 | 0.2 | Not Aware |
| 10 | Leaf | Prediction | 0.4447 | 26 | 0.7 | 0.3 | Not Aware |